Face Mask And Body Temperature Detection In Sensor Enabled Automated Door Control System

Developing an automatic door-opening system that can recognize masks and gauge body temperature is the aim of this project. The new Corona Virus (COVID-19) is an unimaginable pandemic that presents the medical industry with a serious worldwide issue in the twenty-first century. How individuals conduct their lives has substantially changed as a result. Individuals are reluctant to seek out even the most basic healthcare services because of the rising number of sick people who pass away, instilling an unshakable terror in their thoughts.This paper is about the Automatic Health Machine (AHM). In this dire situation, the government provided the people with a lot of directions and information. Apart from the government, everyone is accountable for his or her own health. The most common symptom of corona infection is an uncontrollable rise in body temperature. In this project, we create a novel device to monitor people's body temperatures using components such as an IR sensor and temperature sensor. © 2023 IEEE.

Face Mask and Body Temperature Scanning System for Covid-19

Coronavirus illness 2019 has had a major impact on the entire world over the past two to three years. One important approach for people's protection is to wear masks in public. Furthermore, putting on a mask properly Many public service providers demand that users only utilise the service while properly wearing masks. Only a small number of studies have examined face mask identification using image analysis, nevertheless. We suggest Face Mask, a highly accurate and practical face mask detector, in this study. The suggested Face Mask is a one-stage detector that combines a novel context attention module for detecting face masks with a feature pyramid network to fuse high-level semantic information with various feature maps. We also provide a brand-new cross-class object removal method to reject and predictions with a high intersection of union and low confidence. Additionally, we investigate the viability of integrating Face Mask with a portable or embedded neural network called MobileNet. By utilising1)Contactless temperature sensing,2)we create a fack mask detection alarm system to boost COVID-19 indoor safety.Infrared sensor and contactless temperature sensing subsystems rely on Arduino Uno, while computer vision algorithms are used for mask identification. © 2023 IEEE.

Body Temperature and Oxygen Level Detection System

A device comprising an oximeter and a module for detecting body temperature has been designed so that a person can readily check his or her health in crucial situations. This was accomplished by programming Arduino to output values measured by sensors such as the MAX30102 (Particle Sensor) and GY-906-BCC (Infrared Sensor). We've all been dealing with a global pandemic for the past year. As a result, there have been numerous coronavirus discoveries. The COVID-19 virus primarily affects an individual's respiratory system, lowering the patient's oxygen levels, and it causes a rise in body temperature. This approach can be quite valuable in such situations and can aid in the regular monitoring of an individual's health. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

An IoT Based Smart Vault Security and Monitoring System with Zero UI

Recent advances have introduced IoT as one of the key technologies globally. As safety remains a critical issue for those who spend much time outside. Automated security systems are very useful where safety is an important issue. With a prospect of a Zero User Interface (UI) model this work represents a novel IoT based smart vault security system. The system is built and designed based on IoT combining with Arduino-Uno and Bluetooth module. This system involves LDR sensor, IR sensor and Sonar sensor for monitoring. The vault provides security on three levels. Password protected entry to connect with the smartphone using Bluetooth module, IR sensor array to use 'secret gesture pattern' to unlock the door, tracking number of transactions from the vault using Sonar sensor and LDR was used as a switch. To avoid the replication of physical unlocking of objects IR sensor array was used to introduce 'secret gesture pattern' unlocking system through touchless interfaces for the avoidance of transmissive diseases like COVID-19. This novel system has substantial possibility as a security vault system for industrial and residential use in a contactless manner. © 2023 IEEE.

Arduino based Touchless Temperature Sensing Visitor Notification System

The highly contagious COVID'19 virus's extensive distribution caused the pandemic, which intensified the importance of personal cleanliness and health. Wearing a protective face mask, keeping a certain physical distance, and regularly washing your hands with soap or hand sanitizer are a few precautions you may take to stay safe during this pandemic. An automatic touchless temperature-monitoring doorbell can provide guarded and touch-free temperature sensing, thus informing the household members. The widespread usage of outdated touch-type doorbells may result in the transmission of the coronavirus. The aforementioned article describes a novel approach to creating a Novel Doorbell system that can be activated using gestures and simultaneously detects the person's temperature and notifies the home of a suspected infectious disease. © 2023 IEEE.

Research on 5.5 μm Infrared Filter Applied to Infrared Thermometer

With the expansion of novel coronavirus pneumonia's influence on the world, people's dependence on infrared thermometer guns is increasing. In order to improve the measurement accuracy of the infrared temperature measuring gun and meet the requirements of rapid and accurate measurement of human body temperature, the core components for the infrared temperature measuring gun are developed and prepared in this paper. The film fogging phenomenon caused by the anisotropy of metal germanium and semiconductor properties is analysed and solved by measuring the atomic force microscope image and infrared spectrum of the film, the 5.5-micron infrared filter with high transmittance and good film quality was prepared by electron beam evaporation, resistance evaporation and ion source assisted deposition. © 2022 IEEE.

Robotic Arm Aided Thermal Screening System

With the onset of the Covid-19 pandemic, the health of people has become more of a concern. With this, temperature measurement has gained even more significance. Non-contact thermometers give the advantage of being used in extreme infectious environments, lightweight, repeatability, and many more. Thermal screening helps in identifying people with a high body temperature who are potentially at risk. This research work focuses on the non-contact human body temperature measurement with the assistance of a robotic arm. The robotic arm is used to dispense the power of mobility to the system. The robotic arm, interfaced with Raspberry PI, is used to dispense the power of mobility to the system. Non-contact infrared temperature sensor, MLX90614, is interfaced with Arduino Nano and is used to measure human body temperature. The temperature obtained from the thermal gun is fed to the serial monitor app in the mobile that is connected through the USB cable to Arduino Nano. The temperature sensor's data is displayed on a mobile phone in Celsius unit. The format in which the sensor data is displayed is programmed using Arduino IDE. © 2022 IEEE

Image Recognition Based on Deep Learning with Thermal Camera Sensing

As the COVID-19 epidemic spread across the globe, people around the world were advised or mandated to wear masks in public places to prevent its spreading further. In some cases, not wearing a mask could result in a fine. To monitor mask wearing, and to prevent the spread of future epidemics, this study proposes an image recognition system consisting of a camera, an infrared thermal array sensor, and a convolutional neural network trained in mask recognition. The infrared sensor monitors body temperature and displays the results in real-time on a liquid crystal display screen. The proposed system reduces the inefficiency of traditional object detection by providing training data according to the specific needs of the user and by applying You Only Look Once Version 4 (YOLOv4) object detection technology, which experiments show has more efficient training parameters and a higher level of accuracy in object recognition. All datasets are uploaded to the cloud for storage using Google Colaboratory, saving human resources and achieving a high level of efficiency at a low cost. © 2023 CRL Publishing. All rights reserved.

An Efficient Pulse Detector with Arduino and IR Sensor

For patients to receive good care, doctors must be present. To administer medication or provide treatment, he can't be everywhere at once. If we regularly examine our health, we may be able to identify certain illnesses by spotting them early on. Because of coronary syndromes, many people have died. Doctors are unable to see patients in person until the condition is serious, especially during this period (the Corona virus phase). Because of this, a system to measure pulse rate has been devised in this work. Pulse detection is a straightforward but crucial aspect of keeping track of a patient's health. The hardware used in this research investigates the implementation of a pulse sensor utilising the Arduino development platform and an infrared sensor module created for the Arduino development board. © 2022 IEEE.

Privacy-preserving Social Distance Monitoring on Microcontrollers with Low-Resolution Infrared Sensors and CNNs

Low-resolution infrared (IR) array sensors offer a low-cost, low-power, and privacy-preserving alternative to optical cameras and smartphones/wearables for social distance monitoring in indoor spaces, permitting the recognition of basic shapes, without revealing the personal details of individuals. In this work, we demonstrate that an accurate detection of social distance violations can be achieved processing the raw output of a 8x8 IR array sensor with a small-sized Convolutional Neural Network (CNN). Furthermore, the CNN can be executed directly on a Microcontroller (MCU)-based sensor node.With results on a newly collected open dataset, we show that our best CNN achieves 86.3% balanced accuracy, significantly outperforming the 61% achieved by a state-of-the-art deterministic algorithm. Changing the architectural parameters of the CNN, we obtain a rich Pareto set of models, spanning 70.5-86.3% accuracy and 0.18-75k parameters. Deployed on a STM32L476RGMCU, these models have a latency of 0.73-5.33ms, with an energy consumption per inference of 9.38-68.57\muJ. © 2022 IEEE.

A Deep Learning approach for detection and analysis of respiratory infections in covid-19 patients using RGB and infrared images

Within a short period, the severe acute respiratory syndrome Coronavirus Disease 2019 (COVID-19) has become a devastating global pandemic, causing enormous losses to human civilization worldwide. A significant feature of COVID-19, according to recent investigations, is an altered respiratory state induced by viral infections. In this paper, we present a non-contact method for screening the respiratory health of COVID-19 patients using RGB-infrared sensors to analyze their breathing patterns. The block diagram the proposed method is shown in Fig. 1. First, we use facial recognition to obtain breathing data from the individuals. The respiratory data is applied to multiple neural networks, including LSTM, BiLSTM, GRU, and BiGRU. An attention mechanism is then used in the neural network to obtain a health screening result from the respiration dataset. With an accuracy of 70.83 percent, our BiGRU model accurately identifies the respiratory health condition whether it is normal or abnormal. © 2022 ACM.

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.

Adapting through a Pandemic: Creating a Hands-On Mechatronics Laboratory with Team-Based Collaboration for Remote Learning

This paper introduces a hands-on laboratory curriculum for an undergraduate mechatronics course that delivers a team-based collaborative student experience for remote learning. COVID-19 pandemic created unexpected challenges for educators, where in-person teachings had to quickly transition to remote learning. This significantly impacted learning outcomes for hands-on laboratory courses by students not having access to laboratory equipment and the difficulty to follow the education practice “learn by doing” in the confines of their home. A remote laboratory curriculum is introduced with a series of hands-on mechatronic labs. Three individual student labs introduce how to operate a microcontroller, process infrared sensor signals, and program digital communication displays. Then two team-based collaborative labs explore how students can transmit/receive signals to control a servo using an ESP32 microcontroller with wireless communication over a bi-directional shared server. Then a course project on remote teleoperation is introduced for student-to-student collaboration at home. The learning experience gave students insight into a growing technological area, where teleoperation is in such fields as in-home healthcare, space and ocean exploration, and human-machine collaboration. Student survey results provided positive feedback on their ability to meet project requirements with the challenges of being at home instead of having an in-person learning environment. © American Society for Engineering Education, 2022.

COV-SSDS: Design and Construction of Automatic Social Distancing System to Minimize COVID-19 Infection

Only vaccination can not prevent COVID-19 infection. Social distancing and other preventive measures like - frequent hand washing, wearing a face mask can reduce the rising infection rate of COVID-19. It is not feasible to maintain social distancing and ensure hand sanitization in public places by humans as COVID-19 can affect that person or be contaminated by him/her. An automated social distancing system will play an essential role in maintaining social distance within certain boundaries. An automatic social distancing system called 'COV-SSDS' has been proposed in this work. In COV-SSDS, a person has to disinfect the hands with a sanitizer after being detected by the infrared sensor because the servo motor control door does not open without hand sanitization. If the person does not stand in the proper place, he/she will be notified. A liquid crystal display module has been used to display the number of people in the queue and the occupied slots. An alert generation system to alert the people about occupying the empty slot and a power backup unit was also attached to this system which was not found in previous studies. According to the features, feasibility, maintenance, and cost analysis, 'COV-SSDS' is worthy of the previous works. © 2022 IEEE.

People/Animal Counting - Integrated Sensor Based and Wifi/Machine Learning Based System

Especially with the COVID-19 pandemic, which is affecting the whole world today, accurate determination of the number of people entering a closed area has become very important in terms of measures to be taken against the spread of the disease. This project uses WiFi Signals and IR sensors to determine the number of people in a predefined area. To obtain the required raw data the system utilizes two main principles: the effect of humans on the WiFi signal strength and the entrance-exit control based on distance and LDR sensors. It is a low cost solution with quite good sensitivity and low error level. The simple principles which it is based on allows its application also in other areas like for example livestock farming, where the number of cattle entering a closed area can be counted. © 2022 IEEE.

Design of medical robot control system based on single-chip microcomputer

In order to save manpower, improve the management of COVID-19 prevention and prevent the spread of the epidemic, this paper proposes and designs a medical robot based on a one-chip computer. The single-chip STC89C52 is used as the main control core. Obstacles are detected by infrared sensors. And the robot uses the tracking module to determine the path. The working states of the two DC motors are then changed by the IO-port control L298N drive template, thereby changing the motion state of the robot through the speed difference between the motors on both sides. In the intelligent tracking module, the robot first uses a genetic algorithm to find the best path forward inspection and then enters the ward. After disinfection, the robot uses STM32F4 to drive the OV2640 camera to collect data and detect the mask using the yolov5s algorithm. Finally, it sends the collected information to the computer to realize the real-time monitoring of the patient's condition. The simulation results show that the medical robot can effectively and accurately realize the requirements of path planning, facial mask recognition, and wireless communication. This will significantly improve the efficiency and safety of medical staff. © 2022 IEEE.

Energy-efficient and Privacy-aware Social Distance Monitoring with Low-resolution Infrared Sensors and Adaptive Inference

Low-resolution infrared (IR) Sensors combined with machine learning (ML) can be leveraged to implement privacy-preserving social distance monitoring solutions in indoor spaces. However, the need of executing these applications on Internet of Things (IoT) edge nodes makes energy consumption critical. In this work, we propose an energy-efficient adaptive inference solution consisting of the cascade of a simple wake-up trigger and a 8-bit quantized Convolutional Neural Network (CNN), which is only invoked for difficult-to-classify frames. Deploying such adaptive system on a IoT Microcontroller, we show that, when processing the output of a 8 × 8 low-resolution IR sensor, we are able to reduce the energy consumption by 37-57% with respect to a static CNN-based approach, with an accuracy drop of less than 2% (83% balanced accuracy). © 2022 IEEE.

A Survey on IoT-based Hand Hygiene Dispenser with Temperature and Level Monitoring Systems

Coronavirus flare-up chances human existence and it challenges the general wellbeing. Hand cleanliness, an extremely basic activity, is very much acknowledged to be one of the essential methods of decreasing medical care-related disease and of improving patient security. These days wearing masks, utilizing hand sanitizers, checking temperatures are being done in all places, and so forth yet at the same time in many spots individuals utilize conventional sanitizer gadgets which build the spread of microorganisms. Normally an individual is in charge of observing the body temperature and sanitizer level by taking a chance with his life. This survey Internet of Things (IoT) based hand sanitizer dispenser with temperature and level monitoring distinguishes the presence of the people and gives out alerts in form of the human voice to sanitize their hands if the dispenser goes unrecognized. Furthermore, we have a contactless sanitizer dispenser to stay away from contact among humans and dispensers which will keep us away from the further spread of infection and microorganisms. © 2022 IEEE.

Temperature Monitoring and Application of Machine Learning in Radiology for COVID-19 Pandemic

Entire world got hit by a pandemic due to COVID-19 virus. This virus had a huge toll on the human race which is the reason there is a need to detect such a threat on anearly stage. To detect the virus, some of its symptoms like high fever, cough, cold, and congestion in lungs. Spreading of this virus occurs due to a physical touch between two living or non-living surfaces. Therefore, constant sanitization is required in the contaminated zones. An advanced machine that can take a human X-ray and analyze for infection, check the temperature of the body as well as sanitize while a person is leaving can be a boon to detect cases early. In the entry stage, an X-ray machinewill take a chest X-ray of the person and use machine learning classifiers in order to detect any infection in lungs. On the second stage a temperature monitoring device using infrared sensor will check for high or low temperatures. Alongside, a sterilizing unit having UVC rays will disinfect the person in front of it. In this way, an instant checkup for COVID-19symptoms can help to eradicate the virus. This system can be used for offices, public places as well as medical facilities for detection of the virus. © 2021 IEEE.

News from HAL

[...]based on the improved financial performance and cash flow position, the Credit Rating Agencies CARE Ratings and ICRA Limited have upgraded the Company's credit rating from AA+ Stable to AAA/Stable during the financial year. HAL and BEL sign contract for indigenous IRST HAL and BEL signed a contract for co-development and coproduction of Long Range Dual Band Infra-Red Search and Track System (IRST) for Su-30 MKI on 26 April 2022 under the MAKEII procedure of Defence Acquisition Procedure (DAP) 2020, as part of the 'Make in India' initiative. The proposed IRST system will be a high end strategic technology product in the field of defence avionics and technically competitive to existing IRST system in the global market with features of Television Day Camera, Infrared and Laser sensors in single window for air to air and air to ground target tracking and localisation.