Non-contact Temperature Research Articles

An intelligent spatial stream processing framework for digital forensics amid the COVID-19 outbreak.

In recent times, several strategies to minimize the spread of 2019 novel coronavirus disease (COVID-19) have been adopted. Some recent technological breakthroughs like the drone-based tracking systems have focused on devising specific dynamical approaches for administering public mobility and providing early detection of symptomatic patients. In this paper, a smart real-time image processing framework converged with a non-contact thermal temperature screening module was implemented. The proposed framework comprised of three modules , smart temperature screening system, tracking infection footprint, and monitoring social distancing policies. This was accomplished by employing Histogram of Oriented Gradients (HOG) transformation to identify infection hotspots. Further, Haar Cascade and local binary pattern histogram (LBPH) algorithms were used for real-time facial recognition and enforcing social distancing policies. In order to manage the redundant video frames generated at the local computing device, two holistic models, namely, event-triggered video framing (ETVF) and real-time video framing (RTVF) have been deduced, and their respective processing costs were studied for different arrival rates of the video frame. It was observed that the proposed ETVF approach outperforms the performance of RTVF by providing optimal processing costs resulting from the elimination of redundant data frames. Results corresponding to autocorrelation analysis have been presented for the case study of India pertaining to the number of confirmed COVID-19 cases, recovered cases, and deaths to obtain an understanding of epidemiological spread of the virus. Further, choropleth analysis was performed for indicating the magnitude of COVID-19 spread corresponding to different regions in India.

Study of the up/down-conversion green luminescence of BaWO4: Er3+ phosphors for non-contact temperature sensing and solid-state lighting applications

Study of the up/down-conversion green luminescence of BaWO4: Er3+ phosphors for non-contact temperature sensing and solid-state lighting applications

Temperature-responsive lanthanide-doped nanoarchitecture with orthogonal upconversion luminescence

Lanthanide-doped core-shell upconversion particles with tunable emission bands and intensities in response to external stimuli provide opportunities for multicolor barcoding, optical imaging, and temperature sensing applications. Here, we provide a universal template that can be used as a basic medium for color control and temperature sensing. In a representative nanostructure, i.e., NaYF4:Yb/[email protected]4:Yb/Tm, two excitation-emission spectra-orthogonal luminescence groups with naked-eye observable emission colors (cyan or yellow-green) were obtained by switching the excitation wavelength (980 and 1550 nm). Furthermore, the temperature-responsive optical performance of the nanostructure was investigated, and enhanced temperature sensitivities Sa (0.2339 K−1) and Sr (2.5286% K−1) were achieved based on 3F2,3/4S3/2 non-thermally coupled energy levels (NTCLs). The photophysical properties of the nanostructure show great potential for anticounterfeiting and non-contact temperature sensing applications.

Design Of Non-Contact Human Body Temperature Detection Based On Internet Of Things (Iot) To Open The Door Automatically

Covid-19 has hit Indonesia since March 2020; as a policymaker, the government has imposed new regulations so that everyone can leave the house and do work without worrying about being exposed to the Covid-19 virus. Measurement of body temperature is the fundamental way to determine the condition of body temperature. However, the problem is that when a thermometer is used to check the temperature of the human body, it is still carried out in direct physical contact between humans so that the risk of transmission of the covid-19 virus can occur. Based on these problems, a thermometer was made, which can be used to check human body temperature without making physical contact. Using the prototype method and system design with UML diagrams, the temperature sensor GY-906 MLX90614 (Temperature detection sensor) was used to build a prototype non-contact human body temperature detection monitoring system based on the Internet of Things (IoT) to open doors automatically.). body), LCD (Liquid Crystal Display) displays the results of the human body temperature, servo motor as an action system in the form of a sliding door controller, ESP8266 Wifi Module, which is used as a microcontroller that processes sensor data and sends sensors through a wireless network. The data sent by the ESP8266 Wifi Module can be monitored via a Web application.

Regression model for predicting core body temperature in infrared thermal mass screening.

With fever being one of the most prominent symptoms of COVID-19, the implementation of fever screening has become commonplace around the world to help mitigate the spread of the virus. Non-contact methods of temperature screening, such as infrared (IR) forehead thermometers and thermal cameras, benefit by minimizing infection risk. However, the IR temperature measurements may not be reliably correlated with actual core body temperatures. This study proposed a trained model prediction using IR-measured facial feature temperatures to predict core body temperatures comparable to an FDA-approved product. The reference core body temperatures were measured by a commercially available temperature monitoring system. Optimal inputs and training models were selected by the correlation between predicted and reference core body temperature. Five regression models were tested during the study. The linear regression model showed the lowest minimum-root-mean-square error (RSME) compared with reference temperatures. The temple and nose region of interest (ROI) were identified as optimal inputs. This study suggests that IR temperature data could provide comparatively accurate core body temperature prediction for rapid mass screening of potential COVID cases using the linear regression model. Using linear regression modeling, the non-contact temperature measurement could be comparable to the SpotOn system with a mean SD of ± 0.285°C and MAE of 0.240°C.

Non-Body Contact Thermometer with Voice Output Via Wireless Communication

Currently, thermometer has been widely used by the public. In general, thermometers are designed for people who have normal physical conditions, especially in the ability to see. Disabled people, especially blind people, will find it difficult to use the existing thermometer, especially with the current pandemic situation, which is likely to spread COVID-19 quickly. In connection with this problem, non-contact body temperature measurement is needed with sound output and a wireless system so that there is less possibility of exposure to disease. Therefore, this study describes a non-body contact thermometer with sound output via wireless. The purpose of this study concludes that Non-Body Contact Thermometers can be made with Voice Output Via Wireless to determine normal or hyper and hypo human body temperatures. Thus, this thermometer make it easier for those who have limitations to see and reduce exposure to covid-19 between patients and users. The method in this study employed MLX90614 as a sensor whose output is in the form of digital data, HC-SR04 as a trigger on the MLX90614 sensor, and DF player as a reader on data that have been recorded via Google and stored on the SD card, and XBEE module as transceivers of data to pc. Temperature testing was further conducted by comparing the module with a standard tool, that is a digital thermometer. The error obtained from the module at normal temperature is 0.98%, while the smallest error is 0.1%. Furthermore, in terms of the hypo temperature, the largest error is 1.80%, while the smallest error is 0.42%. Last, at hyper temperature, the largest error is 1.75%, while the smallest error is 0.10%.

Automated Body Temperature, Mask Detection And Face Recognition Based Attendance System

Cross-contamination of the virus among employees is a major risk factor as communities grapple with the COVID-19 outbreak. Swiping cards or bio-metrics are commonly used to track individual employee attendance. This can be a simple means of infection transmission, leading to the virus's spread. If the person is not wearing a mask that can lead to a serious spread of virus. In order to avoid this physical contact for measuring temperature a non-contact temperature gauge can be implemented. This can be used as part of a first examination at entry points to know or avoid people with high temperature to enter the premises, which could also help in order to classify a person who has contracted the COVID-19 infection. This system can be used to as a replacement for the current system, in which a staff is manually scans temperature were the staff is exposed completely to the outsider. The proposed system uses the Haar cascade algorithm for face recognition and temperature of the person is measured along with attendance updation. This eliminates the possibility of virus transmission via card swipes or bio-metrics. The device also identifies whether the employee is wearing a mask and guarantees that the COVID necessary masking protocol is followed

High-sensitive thermometry and tunable dual-color luminescence based on effective energy transfer pathways of Er, Tm system

In this paper, the Er3+,Tm3+ co-doped La2Mo2O9 up-conversion luminescence phosphors are synthesized via solid state reaction. The luminescence characteristics and up-conversion processes of La2Mo2O9:Er3+,Tm3+ phosphors under the excitation of 980 and 1550 nm are investigated in detail. Tm3+ as an important energy transfer medium is the key to effectively improve the population of red-emitting energy levels (4F9/2) in the Er3+ sensitized system. Dual-color luminescence of green and red can be successfully achieved by controlling the concentration ratio of Er3+,Tm3+ co-doping under the dual-wavelength excitation. In addition, the optical temperature sensing ability of La2Mo2O9:Er3+,Tm3+ phosphors is analyzed by employing thermally coupled and non-thermally coupled energy levels. The obtained maximum absolute sensitivities are 8.33 × 10−3 K−1 under the 1550 nm excitation for non-thermally coupled energy levels. The La2Mo2O9:Er3+,Tm3+ phosphors with dual-color luminescence and high temperature sensing ability are the promising candidates in the fields of anti-counterfeiting and non-contact temperature sensing.

Design of Non-Contact Temperature Meter and Automatic Berrier Based On Arduino Uno with C Programming Language

Buddhi College Junior High School is one of the Buddhist schools in Tangerang City in the field of education that requires infrastructure in it. In the era of the Covid-19 pandemic which is increasingly rampant and many activities are dismissed so that it interferes with performance both in terms of education and in the business sector, until in the end many places have to be closed and even have to lose money due to this pandemic, then places must have standard protocols that are met . With this protocol, entrepreneurs and places, one of which is the world of education, need tools that can fulfill the protocol. The lack of knowledge about the symptoms of this disease requires the user to measure his body temperature when entering a place, one of which is a school or university. Temperature gauge is the hotness of an object or object that can be felt. not only used for companies or crowded places, temperature meters can also help health workers to monitor patients easily and quickly. Through the process of understanding until the design process is carried out, an Arduino-based tool design is formed with an algorithm with the c programming language and the workings of the tool to be made. The collected dataset is then sampled for manual processing. The manual process serves to measure the accuracy of the temperature being measured so that it can be implemented on the tool to be made.

Research on the normal emissivity of graphite between 150 and 500 °C by an infrared camera for nuclear fusion devices

• An emissivity measurement equipment by using an infrared camera is constructed and calibrated by a blackbody furnace with a suitable emissivity model. • By using an infrared camera with no filter (band wavelength range of 7.5 μm–13 μm), a 10.2 ± 0.1 μm filter, and a 10.8 ± 0.19 μm filter, the relationship between the temperature and emissivity of graphite and the residual between data and model are obtained respectively and compared. • The emissivity of graphite at different roughness is studied, and uncertainty quantification is used to provide an error estimate for the resulting curves. Due to the advantages of high-temperature resistance, low thermal expansion coefficient, and thermal shock resistance, etc., graphite is regarded as one of the materials for the first wall of nuclear fusion devices. The real-time monitoring of temperature distribution of the first wall based on an infrared camera is widely used to guarantee the stable operation of devices. To accurately measure the temperature of the first wall, it is important to measure the normal emissivity of graphite. However, the emissivity of graphite is affected by many factors. For example, the effect of the surface layers, like carbon-hydro layers-layers, will influence the measurement of the emissivity. The ambition of this work is to study the relationship between graphite emissivity and infrared camera with filters of different wavelengths and the roughness of graphite, and then give the proposed emissivity model to improve the accuracy of graphite surface temperature measurement. The experiment is carried out with a FLIR infrared camera and calibrated by using a blackbody furnace. The emissivity at given temperatures is systematically investigated. By using an infrared camera with no filter (band wavelength range of 7.5–13 μm), a 10.2 ± 0.1 μm filter, and a 10.8 ± 0.19 μm filter, this paper studies the relationship between the temperature and emissivity of graphite from 150 °C to 500 °C and calculates the relative error of temperature measurement respectively. A suitable fitting model which fits emissivity curves is selected. The measurement results show the use of a 10.2 μm filter to measure the graphite surface temperature has the smallest relative error, the range is 0.90%∼1.17%. The emissivity of graphite with different roughness is also studied. At the same temperature, the greater the roughness of the graphite surface, the higher the emissivity value. The uncertainty of the emissivity measurement is analyzed, and its value is 0.0099–0.0211. The graphite surface temperature measurement method based on the emissivity model proposed in this paper provides useful references for the non-contact temperature measurement of the first wall in nuclear fusion devices. The research results can be used as a reference for plasma experiments in some fusion devices and other similar applications.

IoT Based Automated Entry System for Covid Prevention: A Review

Abstract: Since the onset of Covid-19 pandemic, a disease caused by SARS-CoV-2, there has been a significant rise in the research and development for various technologies for the prevention of the pandemic from spreading further. Many technologies like Face Mask Recognition, Facial Recognition, Non-Contact Temperature Measurement, Non-Contact SPO2 measurement systems have been developed with significant quality and efficiency. This paper discusses the results of some of the research done in the same field. Keywords: Facial recognition, Mask Detection, Temperature Measurement, Deep Learning, Convolutional Neural Networks, Sanitizer system, SPO2 measurement, Image Processing.

A Single Subject, Feasibility Study of Using a Non-Contact Measurement to "Visualize" Temperature at Body-Seat Interface.

Measuring temperature changes at the body-seat interface has been drawing increased attention from both industrial and scientific fields, due to the increasingly sedentary nature from daily leisure activity to routine work. Although contact measurement is considered the gold standard, it can affect the local micro-environment and the perception of sitting comfort. A non-contact temperature measurement system was developed to determine the interface temperature using data gathered unobtrusively and continuously from an infrared sensor (IRs). System performance was evaluated regarding linearity, hysteresis, reliability and accuracy. Then a healthy participant sat for an hour on low/intermediate density foams with thickness varying from 0.5–8 cm while body-seat interface temperature was measured simultaneously using a temperature sensor (contact) and an IRs (non-contact). IRs data were filtered with empirical mode decomposition and fractal scaling indices before a data-driven artificial neural network was utilized to estimate the contact surface temperature. A strong correlation existed between non-contact and contact temperature measurement ( > 0.85) and the estimation results showed a low root mean square error (RMSE) (<0.07 for low density foam and <0.16 for intermediate density foam) and high Nash-Sutcliff efficiency (NSE) values (≈1 for both types of foam materials).

Feasibility of Obtaining Surface Layer Moisture Flux Using an IR Thermometer

This paper evaluates the feasibility of a method using a single hand-held infrared (IR) thermometer and a mini tower of wet and dry paper towels to psychometrically obtain surface layer temperature and moisture gradients and fluxes. Sling Psychrometers have long been standard measuring devices for quantifying the thermodynamics of near-surface atmospheric gas–vapor mixtures, specifically moisture parameters. However, these devices are generally only used to measure temperature and humidity at one near-surface level. Multiple self-aspirating psychrometers can be used in a vertical configuration to measure temperature and moisture gradients and fluxes in the first 1–2 m of the surface layer. This study explores a way to make multiple vertical psychrometric measurements with a single non-contact IR temperature sensor rather than using two in situ thermometers at each level. The surface layer dry- and wet-bulb temperatures obtained using an IR Thermometer are compared to Kestrel 4000 Weather Meter and Bacharach Sling Psychrometer measurements under various atmospheric conditions and surface types to test the viability of the method. To evaluate the results obtained using this new approach, standard meteorological surface data are collected during each experiment, and moisture parameters are derived via psychrometric equations. The results indicate that, not only is the method possible and practical, but they suggest that the IR Thermometer method may provide more surface layer temperature and moisture gradient and flux sensitivity than other single instrument methods.

Dielectric and optical evaluation of high-emissivity coatings for temperature measurements in microwave applications

In this work, several commercial high-emissivity coatings have been characterized in terms of emissivity, chemical composition and dielectric properties as a function of temperature, under microwave irradiation. Accurate knowledge of their response under exposure to microwaves provides new and crucial information about their practical usability for non-contact temperature measurements in microwave environments. Due to their high metallic content, some of the studied coatings exhibited unexpected microwave-triggered reactions that hindered their use up to the maximum temperature specified by the manufacturers. Emissivity and chemical analyses before and after the heating cycles confirmed the degradation of some of the samples predicted by dielectric measurements. This work illustrates how a careful characterization of optical and dielectric properties under representative operating conditions (temperature range, microwave exposure) is vital in order to select the appropriate reference coating to obtain reliable temperature measurements in microwave applications.

An IoT-Based Health Monitoring System

Healthcare is a very emerging field nowadays. Wireless sensing and automation are what make a system more reliable and special in the healthcare field. Therefore, the Internet of Things is continuously becoming the stronger part of wireless sensing and monitoring healthcare technologies. Regular monitoring of the heartbeat, SpO2, and body temperature will keep the person aware of his/her health. This system will be working to overcome these three challenges, which include pulse rate, SpO2, and body temperature. Pulse rate and SpO2 will be measured using a pulse sensor and temperature will be measured using a non-contact temperature sensor. This IoT based health monitoring system will display the body temperature, pulse rate, SpO2, and manually assigned user ID of a person (detected using RFID tag) on a server and at the same time, it will also update this information on the cloud using ThingSpeak.

Portable IoT Body Temperature Screening System to Combat the Adverse Effects of COVID-19

In managing the COVID-19 pandemic, the Malaysian government enforced mandatory body temperature screening as a rudimentary form of infection detection at the entry points of establishments and public transportation. However, previous iterations of IoT body temperature screening systems were bulky, fragile, expensive, and designed for personal use instead of the screening of many people. Therefore, a standalone, portable, and rugged IoT-enabled body temperature screening system for detecting elevated temperatures was developed in this research work. This system uses a proximity sensor to detect subjects and determine their body temperature using a non-contact temperature sensor. Body temperature data is displayed on the device and uploaded over a Wi-Fi network to a cloud server for data storage and analysis. From the cloud server, body temperature information is retrieved and displayed on the Blynk IoT client dashboard for remote monitoring. The device also provides alerts for body temperatures above 37.5 °C. The prototype system performed impressively during the assessment. Body temperature readings were impressively accurate compared to a medical-grade non-contact thermometer, with an average variance of less than 1%. Additionally, the system was highly reliable, with a 100% IoT data broadcast success rate.

Optical thermometry based on enhanced up-conversion luminescence in Ba3-yYb4-xO9:xEr3+,yM2+ (M=Mg, Sr, Ca) phosphors

As significantly growing demand for noncontact temperature sensors, the exploitation of superior optical thermometers is increasingly urgency. Herein, novel Ba3Yb4O9:Er3+ phosphors were successfully synthesized and the strategy of appropriate cations substitution (Mg2+, Ca2+, Sr2+) was designed to strengthen the up-conversion luminescence as well as thermometric performance of Ba3Yb4O9:Er3+. Among them, Ba3-yYb4-xO9:xEr3+,yMg2+ is identified to be an excellent optical thermometric material. Based on the fluorescent intensity ratio from thermal coupled energy levels (2H11/2/4S3/2) of Er3+, the relative (SR) and absolute (SA) sensitivities of Ba2.9Yb3.6O9:0.4Er3+,0.1Mg2+ can reach as high as 1.29% K−1 at 302 K and 0.43% K−1 at 573 K, respectively, which are higher than that of Mg2+-free doped Ba3Yb3.6O9:0.4Er3+ (SR:1.15% K−1 at 302 K; SA:0.38% K−1 at 523 K). In addition, the sample exhibits outstanding reversibility and reproducibility. These results imply that Ba3-yYb4-xO9:xEr3+,yM2+ is a promising candidate applied in temperature sensing fields.

Upconversion luminescence and non-contact optical temperature sensing in Ho3+-doped 0.94Na0.5Bi0.5TiO3-0.06BaTiO3 lead-free ceramics

A series of Ho3+-doped 0.94Na0.5Bi0.5TiO3-0.06BaTiO3 lead-free piezoelectric ceramics (NBT-0.06BT: xHo3+, 0.0025≤x ≤ 0.03) are prepared by a conventional solid-state reaction method. Under the excitation of 980 nm, all the samples exhibit strong green, red and near infrared upconversion emissions, which are ascribed to the 5F4/5S2→5I8 (∼547 nm), 5F5→5I8 (∼656 nm), 5F4/5S2→5I7 (∼756 nm) transitions of Ho3+ ions, respectively. The NBT-0.06BT: 0.015Ho3+ ceramic displays the optimal emission among these Ho3+-doped NBT-0.06BT solid solutions. Optical thermometry behavior is evaluated via fluorescent intensity ratio (FIR) of green to red emissions of Ho3+ ions. The temperature sensing performances is investigated in the temperature range of 293–473 K based on non-thermally coupled levels (NTCL). The maximum relative sensitivity is found to be 0.35% K−1 at 293 K. The present investigation results imply the promising application of NBT-0.06BT: Ho3+ in non-contact optical thermometers.

Non-invasive intelligent monitoring system for fault detection in induction motor based on lead-free-piezoelectric sensor using ANN

This paper presents a design of a low-cost integrated system for the preventive detection of unbalance faults in an induction motor. In this regard, two non-invasive measurements were collected then monitored in real time and transmitted via an ESP32 board. A new, flexible, lead-free piezoelectric sensor, developed previously in our laboratory, was used for vibration analysis (VA). An infrared thermopile was used for non-contact temperature measurement. The data is transmitted via Wi-Fi to a monitoring station that intervenes to detect an anomaly. The diagnosis of the motor condition is realized using an artificial neural network (ANN) algorithm implemented on the microcontroller. Additionally, a Kalman filter is employed to predict the vibrations while eliminating the noise. The combination of VA, thermal signature analysis and ANN provides a better diagnosis and provides efficiency, accuracy, easy access to data and remote control, which significantly reduces human intervention.

Research on Operation Management Technology of Cable Joints of Ring Network Cabinet Based on Temperature Sensors

In this paper, aiming at the operation and maintenance of the internal cable joints of the ring main unit, the research on the operation and management technology of the ring main unit cable joints based on temperature sensors is carried out. Starting from the principle of temperature sensing technology for cable joints, an online temperature monitoring system for the cable joints of the ring network cabinet is developed during the operating cycle. Comprehensive consideration of factors such as seasons, ambient temperature and humidity, line load current, etc., to evaluate the operating status of the cable joint temperature data as the main basis. A simple and adjustable bracket suitable for the fixed installation of the non-contact temperature sensor of the ring main unit has been developed. A method of managing the cable joints of the ring main unit during the operating cycle is proposed to realize the effective evaluation of the cable joint status. It can greatly improve the accuracy of condition monitoring, and improve the efficiency and level of operation and maintenance.