Development of a Customized Mask Frame Using a Three-Dimensional Facial Scan for an Airtight Seal for Disposable Surgical Face Masks

Disposable surgical face masks are designed to block the airborne transmission of infectious viruses between patients and healthcare personnel;however, there are limitations to a surgical mask's ability to prevent transmissions because the mask does not provide an airtight seal around the face. This study focuses on the design and development of a custom mask frame, using individuals' three-dimensional (3D) facial scans, to improve the seal of the existing surgical masks. Three participants' facial scans with a wide range of facial dimensions were collected using a 3D hand-held scanner. During design, the contact area between the custom frame and the wearer's skin was determined based on the individual's 3D facial shape. To evaluate the effectiveness of the airtight seal, a qualitative fit (smell/taste) test kit and thermal imaging camera were utilized. When the participants wore the surgical masks without the customized mask frames, the participants smelled the saccharine scent from the test kit. However, while wearing the surgical masks fitted with the custom mask frame that held the mask in place, none of the participants could smell the scent. In addition, thermal images showed ambient temperature changes in the surgical mask suggesting air leakage around the boundary of the mask while the subject was inhaling and exhaling. With the mask frame, thermal images confirmed the effectiveness of the custom frame to block the inflow/outflow of air potentially carrying the virus. The results indicate that the custom-built mask frames are effective in providing a proper and much improved seal compared to a surgical mask without the frame. The developed custom mask frame will be particularly beneficial for frontline medical staff members who treat patients with infectious viruses transmitted through aerosols as part of their PPE.

Stress detection and monitoring based on low-cost mobile thermography.

The high level of stress in modern life is one of the huge problems of the 21st century society, especially in the context of the Covid-19 pandemic. With the pandemic, the need for inexpensive, portable and easy-to-use health monitoring tools (mental and physical) has increased. Of particular importance here is mobile (smartphone) thermography, as it enables the initial detection and self-control of stress, which being intensified nowadays, is the cause of many diseases, depression and health problems. The smartphone thermal imaging camera responds to the strict sanitary guidelines, offering contact-free, painless and non-invasive operation. Additionally, it is included in the group of low-cost solutions available for home use. It is an alternative to commonly used (often expensive and unavailable to everyone): EMG, ECG, EEG, GSR or other high-cost stress detection tools. Thermal imaging by analyzing abnormalities or temperature changes allows for detection application. Therefore, the aim of this work is to determine the possibilities of a low-budget mobile thermal imaging camera in detecting stress, detecting and analyzing stress by identifying the characteristics of psychophysiological signals with the individual characteristics of the participants, along with the correlation. The participants' reactions to the film introducing stress tension up to the climax of the action were recorded thermographically. Data was processed in OpenCV. In the usual observation, stress often remained unnoticed. However, the thermographic analysis provided detailed information on the impact of the film's stressful situation on the participants, with the possibility of distinguishing the stages of stress. The results of the preliminary pilot study were presented, which indicated the variability of temperature and heart rate as important indicators of stress - with the simultaneous significance of individual characteristics of the participant. Smartphone stress thermography is a promising method of monitoring human stress, especially at home.

On the Trail of Some Human Heat. Thermal Imaging, Visual Cultureand the Covid-19 Pandemic

The paper is divided into two main aims. In the first part, it wants to investigate the presence of thermal imaging in the context of contemporary visual culture, especially during the Covid-19 pandemic, when thermal imaging widely demonstrated how currently optics models of vision are increasingly accompanied by thermal models of visualisation. The result of the latter is thermography: at the same time, a process that transforms our epistemic relationship with reality, extending the possibilities of visualising information beyond the limits of the visible spectrum;and an image that maintains the indexical bound with its referent, but that is conceived as the outcome of an elaborated and displayed dataset. In the second part, the paper focuses on the artistic field in which thermal vision gained further relevance in the context of the pandemic. On the one hand, the artists have criticised and deconstructed it;on the other hand, they have relaunched its use in a biopolitical horizon, such as in the case of the photographic project Virus (2020), in which Antoine d'Agata roamed the deserted streets of Paris and visited some intensive care units with a thermal camera, during the first national lockdown in 2020. © 2022 Cinéma & Cie. Film and Media Studies Journal

Roboswab: A COVID-19 Thermal Imaging Detector Based on Oral and Facial Temperatures

The SARS-CoV-2 virus has been the precursor of the coronavirus disease (COVID-19). The symptoms of COVID-19 begin with the common cold and then become very severe, such as those of Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Currently, polymerase chain reaction (PCR) is used to detect COVID-19 accurately, but it causes some side effects to the patient when the test is performed. Therefore, the proposed "Roboswab" was developed that uses thermal imaging to measure non-contact facial and oral temperature. This study focuses on the performance of the proposed equipment in measuring facial and oral temperature from various distances. Face detection also involves checking whether the subject is wearing a mask or not. Image processing methods with thermal imaging and robotic manipulators are integrated into a contact-free detector that is inexpensive, accurate, and painless. This research has successfully detected masked or non-masked faces and accurately detected facial temperature. The results showed that the accurate measurement of facial temperature with a mask is 90% with an error of +/-0.05%, while it was 100% without a mask. On the other hand, the oral temperature was measured with 97% accuracy and an error of less than 5%. The optimal distance of the Roboswab to the face for measuring temperature is an average of 60 cm. The Roboswab tool equipped with masked or non-masked face detection can be used for early detection of COVID-19 without direct contact with patients. © 2023, Politeknik Negeri Padang. All rights reserved.

Machine learning based human body temperature measurement and mask detection by thermal imaging

The worldwide impact of the COVID-19 epidemic has been immense. Economic, educational, industrial, and other sectors all took a hit as a result of COVID-19. Unaware of how to address this, the health care industry was also hit. In the absence of a known cure, the most effective way to slow the spread of this fatal illness is to wear a face mask when doing so. Wearing a face mask when in public or conversing with people is also mandated by the WHO. Additionally, the most common symptom is high fever, which occurs in those who are unwell with this condition. As a result, we describe a system that can distinguish face masks using a regular RGB camera and identify persons with high body temperatures using a thermal camera with an 80x60 resolution. Tracking safety violations and encouraging the use of face masks may be achieved by using this method. © 2022 IEEE.

Thermal Screening Solution Using Infrared Thermography and Closed-Circuit Television

Closed-circuit television camera (CCTV) and thermal imaging devices are used to detect febrile individuals entering establishments for Coronavirus 2019 (COVID-19) containment. Real-time tracking in post-COVID is manually checked by security personnel, which has risks of less efficiency due to human errors, as advance thermal cameras are unaffordable for some business owners. The main goal is converting an installed CCTV interfaced with infrared sensor to develop an economical thermal screening system with acoustic alarm. In this project, the colored and heatmap images transmitted from the thermal camera were processed through OpenCV. A calibration method was also performed to validate the temperature reading from the thermal camera. The project comes with graphical user interface (GUI) connected into a database, which visually tracks individuals exhibits elevated body temperature. The performance of the system shows above 95% accuracy upon conducting an inexpensive calibration check. The significance of this project is highlighting the effective mitigation of virus spread which offers safe and contactless analysis of potential individuals showing early symptoms of COVID-19. Additional features can be added for future work such as facemask detector, multiple thermal camera setup, and Login Options making the device and application exclusively for business owners. © 2022 IEEE.

Infrared Thermal Imaging Face Recognition Method Based on Temperature Block Feature

In order to prevent COVID-19 effectively, non-contact body temperature measurement and human identification are required in public places, but face recognition based on visible light cannot meet the requirements. Therefore, this paper proposes a thermal imaging face recognition method based on temperature block feature extraction. Histogram equalization and median filter are used to preprocess the face image, and Sobel operator is used for face detection;Six dimensional features including temperature mean, standard deviation and adjacent difference are extracted from each temperature block in the average poolinged temperature matrix, and classified by max-correlation-coefficient method. The experimental results show that the recognition rate of this method is 6.1% higher than that of PCA method with the temperature block size of boldsymbol{2times 2}. When using the same hardware to execute the program, if the two recognition rates are very close, the average test time of the proposed method is 22.2% less than the one of deep learning models such as Alexnet. Furthermore, the proposed method has strong robustness for small training sample set. For example, the recognition rate of single training sample model can reach 0.7, while in the deep learning model, except Mobilenet can reach 0.6, all of the others are less than 0.4. © 2022 IEEE.

Analysis of the influence of external conditions on temperature readings in thermograms and adaptive adjustment of the measured temperature value

Measuring human temperature is a crucial step in preventing the spread of diseases such as COVID-19. For the proper operation of an automatic body temperature measurement system throughout the year, it is necessary to consider outdoor conditions. In this paper, the effect of atmospheric factors on facial temperature readings using infrared thermography is investigated. A thorough analysis of the variation of facial temperature with the prevailing atmospheric conditions was carried out using recordings collected over two years and compared with air temperature values at 1 hour accuracy. A method that takes account of outdoor conditions on temperature readings was proposed. We developed a correction curve with coefficients values based on an analysis of the recordings of people entering the building. Such a method will allow an effective real-time fever screening in public places. © 2022 IEEE.

Non-contact measurement system for COVID-19 vital signs to aid mass screening—An alternate approach

The entire world is facing a pandemic after the COVID-19 outbreak reported in Wuhan City in China. The number of newly infected cases and deaths are increasing on an hourly basis. The birth and spread of the n-coronavirus is a mystery to the world. Social distancing, staying home, and washing hands frequently with soap and water are the present norms for not getting infected or spreading it. The symptoms of a COVID-19 infected person are high fever, nasal congestion, aches and pains, difficulty in breathing, loss of smell and taste, and sore throat. The standard approach for screening any COVID-19 patient is to measure the body temperature, usually by infrared temperature sensors. This primary indication makes the person to be required to undergo the COVID-19 test. In most of the cases, the test results provide false positive and true negative kind of misclassification. Delay in finding the COVID-19 carriers makes it a challenging task for any healthcare administration to reduce the growth of positive cases. Few more vital signs like heart rate, oxygen saturation, respiratory rate, and body temperature are more relevant to make the person take the COVID test. In most of the screening tests at crowded places like airports, railways stations, and industries, the primary signs vital in detecting COVID are missed. Moreover, the measurement of all these physiological parameters requires dedicated measuring devices and skilled healthcare professionals. The cost of implementation and procurement gives more financial burden during this economic crisis. An alternate approach to measuring all these vital signs is extracting feature points from the thermal and or visible light reflected from the face of subjects. These feature sets are given to convolutional neural network (CNN) models for training and the trained model can predict the signs from the test inputs. The preliminary readings would be instrumental in suggesting the person undergo the COVID-19 test. It will also act as a continuous monitoring system to read the health condition of vulnerable and treatment undergoing persons. Such systems can be incorporated in any surveillance system and immigration zones to find overseas travelers’ health conditions. The risk of affecting healthcare field workers can be reduced. The possible implementation of health drones creates a pathway to Tele-diagnosis. © 2022 Elsevier Inc. All rights reserved.

Novel Wearable Thermal-Color Dual Modal Imaging System for COVID-19 Temperature Screening

The ongoing COVID-19 pandemic has devastated communities and disrupted life worldwide. Thermal imaging systems are beneficial for temperature screening as the operator of the thermal imaging system is not required to be physically close to the subjects, in contrast to the contact thermography approach. In addition, thermal imaging systems typically measure surface skin temperature faster than the typical forehead or oral thermometers. One of the greatest challenges of COVID-19 is effective screening of schools, universities, and military units, where there are large gatherings of population. For rapid and high-throughput temperature screening, a wearable system is advantageous as wearable systems can enable hands-free operation and allow the operator to move around freely. In this study, we developed a prototype wearable system capable of real-time thermal-color dual- modal imaging with 3D augmented reality capability. We have also demonstrated a new method to register thermal and color imageries independent of working distance and object features. The portable nature and AR display can potentially enable on-the-go screening.

Evaluation of Adjustment Models for Taking Body Temperature with a Thermal Imaging Camera in the Context of COVID-19

In the context of the COVID-19 health emergency, it is necessary to have devices that help identify symptoms that indicate whether a person has COVID-19. As one of the main symptoms is fever, which can be identified by measuring body temperature, different non-contact measurement methods are being widely used as an alternative to traditional contact thermometers. However, readings with thermographic cameras present limitations in terms of high dependence on the environment. For this reason, this article aims to validate the temperature measurements of a thermographic camera by comparing different models using as a reference standard the readings of a calibrated medical infrared thermometer. For this purpose, 463 measurements were analyzed using an infrared thermometer and a thermographic camera simultaneously. As significant differences were observed between the measurements made using statistical analyses with (p< 0.05 ), models were developed establishing weighting and compensation criteria to obtain similar readings between the values measured from the thermal images and the infrared thermometer. For uncertainty estimation, linear and non-linear regression models such as artificial neural networks were tested, selecting the best model that allows reducing the variation among the readings. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Smart Access Control System For Covid Safety Smart Access Control System during Covid

During the period of prevailing unsettled COVID pandemic, the countries and states started to plan reopening during which necessitates the non-contact temperature evaluation gadgets as a part of a preliminary look at access points to identify the humans with elevated body temperatures. Despite the utilization of these devices, temperature assessment restricted the impact on lowering the spread of COVID-19. Non-contact temperature measuring devices are used to measure the temperature of any person. Detection of a high temperature is one huge manner to pick out a person who might also have COVID-19 contamination. In this project, a room environment is created in which certain precautions are taken. A laser diode and receiver are used to detect the entrance of a person, and the system also detects the body temperature of the entering person. If the temperature is less than a threshold temperature entry for the person is permitted or else the entry is denied. This system also has a feature where it permits only a pre-determined number of persons inside the room. It also facilities to view the allowed temperature, the number of people to be allowed in the room and the number of people present actively using a Bluetooth App. This system aimed to be useful to combat the spread of COVID infections. © 2022 IEEE.

Thermal Imaging-Based Body Temperature and Respiratory Frequency Measurement System for Security Robot

Measurement of body temperature and respiration rate is the most basic screening in knowing a person's health. For security reasons and to prevent the spread of transmission, in the Covid-19 pandemic conditions, measurements can be made by security robots. Measurement of body temperature and respiration rate was done non-contact based on thermal imaging. Temperature measurement is based on the temperature in the face area, while the respiration rate is based on changes in temperature in the nose area. The ability to measure temperature gives an accuracy of 98.21% with a standard deviation of 0.536. And the best respiration rate is the fast Fourier transform method which gives an accuracy of 79.8% with a standard deviation of 3.291. © 2022 Wydawnictwo SIGMA-NOT. All rights reserved.

MONITORING HELMET—The Use of Thermal Imaging to Monitor the Epidemic Threat Caused by the Corona Virus

The objective of an interdisciplinary team of IT specialists, bio-engineers, architects, a specialist in thermovisual measurements and medical personnel was to develop an apparatus enabling a remote measurement of human temperature using a thermal imaging camera coupled with a mobile phone and the Augmented Reality technology. The team designed a portable device which makes it possible to conduct measurements in an automatic way without the use of hands. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Low-cost thermal imaging with machine learning for non-invasive diagnosis and therapeutic monitoring of pneumonia.

Rapid screening and early treatment of lung infection are essential for effective control of many epidemics such as Coronavirus Disease 2019 (COVID-19). Recent studies have demonstrated the potential correlation between lung infection and the change of back skin temperature distribution. Based on these findings, we propose to use low-cost, portable and rapid thermal imaging in combination with image-processing algorithms and machine learning analysis for non-invasive and safe detection of pneumonia. The proposed method was tested in 69 subjects (30 normal adults, 11 cases of fever without pneumonia, 19 cases of general pneumonia and 9 cases of COVID-19) where both RGB and thermal images were acquired from the back of each subject. The acquired images were processed automatically in order to extract multiple location and shape features that distinguish normal subjects from pneumonia patients at a high accuracy of 93 % . Furthermore, daily assessment of two pneumonia patients by the proposed method accurately predicted the clinical outcomes, coincident with those of laboratory tests. Our pilot study demonstrated the technical feasibility of portable and intelligent thermal imaging for screening and therapeutic assessment of pneumonia. The method can be potentially implemented in under-resourced regions for more effective control of respiratory epidemics.

Detecting Essential Landmarks Directly in Thermal Images for Remote Body Temperature and Respiratory Rate Measurement With a Two-Phase System

Infrared thermographs (IRTs, also called thermal cameras) have been used to remotely measure elevated body temperature (BT) and respiratory rate (RR) during infectious disease outbreaks, such as COVID-19. To facilitate the fast measurement of BT and RR using IRTs in densely populated venues, it is desirable to have IRT algorithms that can automatically identify the best facial locations in thermal images to extract these vital signs. The IEC 80601-2-59:2017 standard suggests that the regions medially adjacent to the inner canthi of the eyes are robust BT measurement sites. The nostril regions, on the other hand, are often used for RR estimation. However, it is more difficult to automatically identify inner canthi and nostrils in thermal images than in visible-light images, which are rich with exploitable features. In this paper, a unique system that can detect inner canthi and outer nostril edges directly in thermal images in two phases is introduced. In Phase I, original thermal images were processed in four different ways to enhance facial features to facilitate inner canthus and nostril detection. In Phase II, landmarks of the inner canthi and outer nostril edges were detected in two steps: (1) face detection using the Single Shot Multibox Detector (SSD) and (2) facial landmark detection to locate the inner canthi and outer nostril edges. The face detection, facial landmark detection, and overall system accuracies were evaluated using the intersection over union, normalized Euclidean distance, and success detection rate metrics on a set of 36 thermal images collected from 12 subjects using three different IRTs. Additional validation was performed on a subset of 40 random thermal images from the publicly available Tufts Face Database. The results revealed that the processed images - referred to as ICLIP images - yielded the highest landmark localization accuracy from the four types of processed thermal images, verifying that the system can automatically and accurately estimate the inner canthus and nostril locations in thermal images. The proposed system can be applied in IRT algorithms to provide reliable temperature measurements and RR estimates during infectious disease outbreaks. © 2013 IEEE.

Studying the accuracy of infrared thermography for measuring core body temperature

The purpose of this study was to investigate the accuracy of infrared thermography for measuring body temperature. We compared a commercially available infrared thermal imaging camera (FLIR One) with a medical-grade oral thermometer (Welch-Allyn) as a gold standard. Measurements using the thermal imaging camera were taken from both a short distance (10cm) and long distance (50cm) from the subject. Thirty young healthy adults participated in a study that manipulated body temperature. After establishing a baseline, participants lowered their body temperature by placing their feet in a cold-water bath for 30 minutes while consuming cold water. Feet were then removed and covered with a blanket for 30 minutes as body temperature returned to baseline. During the course of the 70-minute experiment, body temperature was recorded at a 10-minute interval. The thermal imaging camera demonstrated a significant temperature difference from the gold standard from both close range (mean error: +0.433°C) and long range (mean error: +0.522°C). Despite demonstrating potential as a fast and non-invasive method for temperature screening, our results indicate that infrared thermography does not provide an accurate measurement of body temperature. As a result, infrared thermography is not recommended for use as a fever screening device. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.

AVIATION & DEFENCE In India

MoD and Make in India scheme Many significant projects including 155mm Artillery Gun system 'Dhanush', Bridge Laying Tank, Light Combat Aircraft 'Tejas', 'Akash' Surface to Air Missile system, Submarine 'INS Kalvari', Inshore Patrol Vessel, Offshore Surveillance Ship, 'INS Chennai', Anti-Submarine Warfare Corvette (ASWC), Arjun Armoured Repair and Recovery Vehicle, Landing Craft Utility, Bridge Laying Tank, Bi-Modular Charge System (BMCS) for 155mm Ammunition, Thermal Imaging Sight Mark-II for T-72 tank, 25 ? Airbus signs contract with BEL for C295 programme As part of its offset commitments under the prestigious C295 aircraft programme of the Government of India, and in line with the 'Make in India' policy, Airbus Defence and Space has signed a contract with Bharat Electronics Limited (BEL) for the manufacture and supply of Radar Warning Receiver (RWR) and Missile Approach Warning System (MAWS). The order spanning five years from 2023 to 2028 involves supply of critical avionic Line Replaceable Units (LRUs) related to Digital Flight Control Computers, Air Data Computers, Weapon Computers, LRUs related to Radar Warning Receiver (RWR) and Head Up Display. First sea sortie of fifth scorpene submarine 'Vagir' The fifth submarine of Project 75, Yard 11879, Indian Navy's Kalvari class commenced her sea trials on 1 February 2022.

Development of a Low Cost and Raspberry-based Thermal Imaging System for Monitoring Human Body Temperature

Since 2020, COVID-19 had caused about millions of deaths and huge economic losses in the world. Taiwan had a successful story of preventing COVID-19 invasion. Unfortunately, COVID-19 broke down the preventing a couple of months ago. In addition, Taiwan doesn't have enough the vaccines to stop the COVID-19 spreading. This event really let Taiwan people to live painfully and inconveniently every day. However, it is really needed a system assist Taiwan people to prevent from the COVID-19 attack. According to this need, we attempt to develop a thermal imaging which is capable of detecting the people with fever. The price of thermal imaging system is usually very high. Most of companies or organizations can't afford it instead of a cheap forehead gun. Although forehead gun can precisely measure human body temperature, its inconvenient usage increases employees' loading. This paper presents the development of the low cost thermal imaging system. The system consists of PureThermal Mini/FLIR Lepton 3.5, Raspberry cam, and Raspberry pi 4. The PureThermal Mini is a thermal module with smart I/O. It has a FLIR Lepton3.5 thermal imager. The thermal imager can provide the system a thermal image with the resolution 160×120. Currently, its price is around 15,000NTD. The resolution of the thermal image is quite low. In order to fit the need of the system, an image resize algorithm is applied to create a large size of thermal image for further application. About Raspberry Cam, it is a regular cam which can be directly installed on Raspberry Pi. Its resolution is up to 2592×1944 and its cost is about 1,500NTD. Its image can supply the system to deal with Artificial Intelligence process, such as human facial recognition. Raspberry Pi 4 is the core controller of system. It contains our developed Python program which is used to handle all of system processes. 3D printing is also applied to build the structure frames of the system. The cost of the developed system is less than 20,000NTD. It is capable of detecting more than two people simultaneously and automatically. With the assistance of the system, companies or organizations can efficiently protect their employees away from the attack of COVID-19. © 2021 IEEE.

COVID-19 suspected person detection and identification using thermal imaging-based closed circuit television camera and tracking using drone in Internet of Things

COVID-19 has emerged as a worldwide health concern. It is very hard to check or scan every individual. In this paper, we have propounded a system where the suspected person can be easily detected and identified for COVID-19 by using thermal imaging-based closed-circuit television. The thermal imaging-based closed-circuit television will automatically scan the person in vicinity and capture the video/image of the suspected person. The system will raise an alarm in the vicinity so that people in vicinity keep clear of each other. The recorded video/image will be forwarded to the base station and information about the suspected person will be fetched from the server. Meanwhile, the drones will be used for tracking the suspected person until the nodal medical team diagnoses the suspected person for confirmation. The proposed system can contribute significantly to curbing the rate of infected COVID-19 persons and prevent further spread of this pandemic disease.