ABSTRACT
Considering the public safety in current COVID-19 out-break, an IOT (Internet of Things) based non-contact temperature monitoring system integrated with RFID authentication system with an interactive Android application, and a web-portal to manage users and temperature records has been proposed. Temperature screening has become essential for all the industries, educational institutions, factories and corporate sector. This system is an online real-time non-contact monitoring system with an interactive android application and user-friendly web portal that help end-users to monitor and keep a record of temperature variations of registered users on daily/weekly/monthly basis. The temperature records are saved in a real-time database which is embedded with the user's RFID card information. In case of an alert (high temperature), a notification is sent to the authorized personnel on their cellphones or their desktop systems via web portal. An alarm is also generated immediately on the device (buzzer and blinking LEDs) to indicate high temperature, alerting the nearby security staff. As per the survey and testing of the device under different temperature environments it has been found that the proposed system has an overall accuracy of 99%. © 2022 IEEE.
ABSTRACT
Over the past two years, COVID-19 has spread over 200 countries, leading to pandemic proportions. Still, the virus is rapidly changing, the variants spreading through direct and indirect contact in places irrespective of the vaccine distribution. Many infectious diseases spread through droplets, and micro-droplets require face masks and other social distancing measures. This article proposed for pandemic circumstances called real-time face mask with health screening (RTFMHS) with two screening methods: (i) Internet of Things (IoT) node monitors a real-time intelligent face mask detection using multi-level high-speed augmented convolution neural network (MLHS-CNN), (ii) Individuals health indicators such as non-contact body temper-ature sensor and blood oxygen saturation are sending to fog cloud to manipulate and display the user health status. A face mask detection technique based on MLHS-CNN is proposed to determine whether a person is wearing a mask properly. User health is computed in real-time by an RNN running on the fog server to estimate the risk of infection spreading. The proposed method uses a lightweight IoT node and fog-based Deep Learning (DL) tools for data analysis and diagnosis. The experimental results outperformed previous research in terms of detection accuracy, precision, recall, and time complexity. © 2022 IEEE.
ABSTRACT
An automated temperature scanner with contact-tracing capability had previously been developed to screen temperature related diseases such as COVID-19, Ebola or Lassa fever and trace possible infected persons. The device uses a non-contact temperature sensor (MLX-90614) to acquire human temperature while the user's identity is obtained by means of Radio Frequency Identification card. This information is sent for storage in remote database and made available for possible contact-tracing via a secured web interface. Due to the fact that several studies contest the validity of non-contact temperature sensors as replacement for contact ones, the present study therefore compares performance of its non-contact temperature sensor with that of the mercury-in-glass thermometer considered as a standard in this study. This is in an attempt to validate performance of the developed automated temperature scanner and to optimize its usage. Investigations reveal that the developed device performs best when user is within a 16 cm distance from the temperature sensor. Any measurement done outside this 16 cm critical distance might not be valid. Other investigations reveal that the developed device with non-contact temperature sensor is faster than the contact thermometer with an average response time of 0.004 second compared with mercury-in-glass of 179.2 seconds. So non-contact sensor would be very useful when speed is of essence but it was found to exhibit a lower precision compared to the contact thermometer. The critical temperature obtained in this study will guide users in the usage and researchers in further studies on the developed automated temperature scanner with contact-tracing capability. © 2022 IEEE.
ABSTRACT
This project is to intimate start and stop time of a particular session with the help of buzzer. A faculty keep on taking his lecture continuously. If the lecture was interesting and engaging the session will be keep on going. Buzzer is used to intimate when will be the session starts and when it will be going to end. Here timing will be predefined. Next one major challenge in schools and colleges is to take attendance manually. For taking attendance with the help of using fingerprint sensor-R307.Here the fingerprints of each and every individual student were stored in the fingerprint sensor itself. If the student keeps his fingerprint, then the particular student attendance is marked. It will only mark attendance if particular person keeps his unique fingerprint. Due to COVID-19 pandemic, central and state government announced to monitor the body temperature of each and every student on daily basis. For monitoring body temperature with help of using Non-contact temperature sensor-MLX90614. We place the temperature sensor near to the fingerprint sensor. If a student comes and keep his fingerprint his attendance will be marked and then he wants to keep his hand to measure his body temperature. If the body temperature of particular student is high means it will displayed in OLED display. To intimate a particular session to the staff. Sometimes staffs have some other work while doing their work they may forget their session. To intimate the session to the staffs by triggering mail or message to the staff. © 2022 IEEE.
ABSTRACT
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.
ABSTRACT
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.
ABSTRACT
The world is currently facing a pandemic attack of Coronovirus disease (COVID-19), which is an infectious disease causing mild to moderate respiratory illness. One of the most common and early symptoms of COVID-19 is fever which is the reaction to a disease-specific stimulus causing the increase of the human body temperature. To slow down the transmission of the COVID-19 virus, the public is required have their body temperature measured when entering any premises. The current common method of monitoring the human body temperature uses the application of non-contact infrared thermometer (NCIT) and is only limited for stationary conditions within short distances and mostly suitable for indoor premises. The available technology to detect human body temperature for longer distances uses the thermal camera which is costly and large. Thus, it is challenging to detect anyone with high body temperature is non-stationary conditions, at longer distances, especially outdoor. The project proposes an innovation to the current practice, for a wearable noncontact temperature detector device which is portable. The wearable non-contact temperature detector embeds a thermal sensor and a microcontroller to a normal hat. It is able to detect objects with higher temperature (37.5°C) within 1 meter radius of 60° angle view in stationary and non-stationary conditions. The wearable device communicates via Bluetooth to a mobile device to display the detected temperature and notifies the user via alert message and alarm for high temperature detection. Display of the object's thermal image is also available with a resolution of 8 times 8 pixel. The wearable non-contact temperature detector is able to achieve 99% accuracy of temperature measurement for detection distance of up to 70 cm for indoor and within 20 cm for outdoor when tested with normal temperature subject and high temperature object and compared with the actual temperature detected via a commercial NCIT device. © 2021 IEEE.
ABSTRACT
Infrared thermography thermometer is a non-contact temperature measuring equipment, which is widely used in the stage of large-scale epidemic of the covid-19 pandemic. It is used for rapid screening of human body temperature in crowded places at the entrance and exit of airports, docks, shopping malls, stations and schools. But when the outdoor temperature approaches or exceeds the body temperature in summer, can this method of measuring body surface temperature by infrared thermal imager be used as a standard for screening fever? Under the condition of high temperature in summer, the field experiment of measuring body temperature by infrared thermal imager is carried out, the experimental results are analyzed. We recommend the use of relative temperature difference for screening patients with fever. © 2021 Institute of Physics Publishing. All rights reserved.