ABSTRACT
The article introduces a novel strategy for efficiently mitigating COVID-19 distribution at the local level due to contact with any surfaces. Our project aims to be a critical safety shield for the general people in the fight against the epidemic. An ultrasonic sensor is integrated with the automated doorbell system to ring the doorbell with a hand motion. A temperature sensor Mlx90614 is also included in the system, which records the temperature of the person standing in front of the door. The device also includes a camera module that captures the image of the person standing at the front entrance. The captured image is processed through an ML model which runs at over 30 fps to detect whether or not the person is wearing a mask. The image and the temperature of the person standing outside are sent to the owner through the configured iOS application. If the person outside is wearing a mask, one can open the door through the app itself and permit the entry of the person standing outside thereby integrating the edge device with an app for a better user experience. The system helps in reducing physical contact, and the results obtained are at par with the already existing solutions and provide a few advantages over them. © 2023 the author(s), published by De Gruyter.
ABSTRACT
COVID-19, is caused by the transmission of SARS-CoV-2 through direct or indirect contact with infected people though respiratory droplets has transitioned from a pandemic to an endemic but is still regarded as active by WHO. Restrictions and lockdowns were lifted as the situation became endemic, but the previous measures had to be kept in place. By developing a module that includes temperature monitoring, face mask detection, a non-contact sanitizer dispenser, and door automation that operates based on the number of individuals inside a closed area in order to maintain social distance, our project aims to incorporate these precautions into our everyday language. As a part of making the new normal easily adaptable, we also introduce a webpagebased reservation system, which wm essentially display the current count and also help in reducing the waiting periods. © 2023 IEEE.
ABSTRACT
Globally, atmospheric carbon dioxide (CO2) concentration is rising due to rising carbon-based fuel consumption and ongoing deforestation. As carbon dioxide levels grow due to the warming trend, the atmosphere's temperature is predicted to climb. Increased fatigue, headaches, and tinnitus are just a few health issues that high CO2 concentrations in the atmosphere can cause. The electrical activities of the brain, the heart, and the lungs have all been demonstrated to change significantly after a brief exposure to 0.1 percent CO2. Continuous measurements of the atmospheric CO2 content have recently been shown to help evaluate the ventilation conditions in buildings or rooms. Additionally, it prevents the development of the severe acute respiratory syndrome coronavirus 2 (Severe acute respiratory). The coronavirus, known as a powerful acute respiratory, can make people ill. This has grown to be a significant concern in emergency medicine. © 2022 IEEE.
ABSTRACT
The present Covid-19 pandemic, face mask detection identifying significant forward movement in the fields of image and computer observation. Several face detection models were developed utilizing various methods and techniques. The dataset arrangement supplied in this work, which was gathered from multiple sources, could be utilized by other to develop more complex representation such as those for facial identification software, facial positions, and facial component identification. The goal of project 'Real Time AI Based Face Mask Detector', It is develop a tool that really can identify a person image and to affect whether he or she is wearing a mask. COVID makes it necessary to wear a face mask to keep it safe. As the country begins to reopen in stages, face masks have become a crucial part of our everyday life to keep safe. Face masks will be essential for socializing and conducting business. As a result, this software uses a camera to notice whether a person is wearing a mask or not. © 2022 IEEE.
ABSTRACT
There was global shock from COVID-19 epidemic. Social isolation is becoming more crucial as this delicate condition spreads swiftly. Public transit must be enhanced to stop the spread. This paper proposes an IoT method using LoRa technology that might reduce overcrowding and disease transmission in public buses. In the proposed, buses shall have LoRa transmitters and receivers. It is shown on the bus stop's LCD screen and announced over a speaker if the bus is within range of the receiver. An automatic door mechanism limits the number of people inside the vehicle. In the mobile app, the bus occupancy data is sent to Google Firebase. The app also indicates nearby buses, their occupancy, and their estimated arrival time. In certain cases, authorities may utilise this data to analyse and act. This simple technique would improve bus safety and contain COVID-19.
ABSTRACT
During the Covid-19 pandemic, there was an increase in the use of electrical energy on a household scale. This study developed a home-scale power monitoring system to monitor electrical power at a household scale. This research was conducted to facilitate access to home power monitoring via Android based on the Internet of Things using the Thinger.IO web browser and Telegram Messenger using the Bot feature. This power monitoring system develops using the ACS712 sensor as a current reader and the ZMPT101B as a voltage reader, using an ESP32 microcontroller with a WiFi module that can be connected online. The results of this study are that the accuracy of the ZMPT101B voltage sensor is excellent, with an accuracy value of 99.845%. The ACS712 current sensor has the highest difference value with a reference of 0.32 A and 0.04 A for the lowest difference value. The data logger system on Thinger.IO works well in recording data. The Bot Feature on the Telegram application can work well even though it has an average delay of up to 4.2 seconds, depending on the speed of the internet network. © 2022 IEEE.
ABSTRACT
The need for intelligent and distributed monitoring systems based on sensor networks of diverse application systems is growing as a result of the field of industrial control in network applications developing so quickly. It is required to check the body temperatures and attendance when students and staffs visit schools and colleges during this COVID 19 pandemic. A solution is developed here for the purpose of tracking temperatures and attendance management using a smart thermometer without being in contact in order to keep social distance. The person (both staff and student) faces are captured by the ESP32 Camera for training and testing purposes. After the training is over, the ESP32 Micro Controller board registers the student or faculty facial image. For attendance purposes, the MLX90614 IR Temperature Sensor will measure the body temperature of students or instructors. Both the collected data and the email-based attendance notification will be transferred to the cloud using IoT. The message "Please leave the college and take care of your health" will be communicated to the person if their temperature exceeds the threshold level. © 2022 Authors. All rights reserved.
ABSTRACT
Quarantine is the process of restricting and separating the movement of people who have been exposed to a contagious disease to avoid proliferation. Quarantined subjects were monitored manually, and patients tended to abscond or 'run away.' In the Philippines, there was a lack of research and the absence of similar technology commercially available related to this matter. Project Bantay integrated Artificial Intelligence of Things (AIoT), indoor positioning systems, and wearable technology to alleviate the shortage of personnel, long-Term savings on workforce utilization in the government, and predict absconding or 'run-Away' potentially infectious individuals in our current and future quarantine facilities. Also, it included information system development for monitoring quarantined subjects' heart rates and temperatures that would eventually help the government combat and prepare for a similar unexpected pandemic. The prototype would start by turning on the device after being placed on the quarantined subject. The device must be linked to the router, and the sensors must then be calibrated. The web interface should receive and be able to see data readings, including temperature, heart rate, the location of the subject being quarantined, and the removal of the device via an IR reading. The temperature, heart rate sensor, and indoor positioning all measured above a p-value of 0.05, which accepted the null hypothesis, confirming that the actual and commercial product versus Project Bantay's temperature, heart rate, and indoor positioning accuracy was statistically the same. The anti-Absconding tendencies of the hypothetical dataset using machine learning data analytics showed that among four inherently multioutput machine learning regression algorithms, the Decision Tree Regression Algorithm could output a much better result in determining the tendencies of a subject to abscond from the quarantine facility. © 2022 IEEE.
ABSTRACT
In this paper, we propose a model named Virtual Doctor- Teleconsultation and Parameter Monitoring System' which provides some usefulness of providing medication and helps in gauging the essential parameters (Heart rate, Temperature and SpO2) and UVC (Ultraviolet sort C) sterilization unit for the sensors. During the ongoing situation, diminishing the human-to-human contact in emergency clinics is required. In a bid, to keep specialists and clinical staff from getting impacted by Coronavirus, the job of medication conveying robots are being developed. We can attain the Locomotion procedure of the robot using telegram bot and live video streaming by ESP32-Camera. The working principle is that the Doctor or the Nurse can control the moment of entire model by observing surroundings using a camera and commanding through a mobile application. For this model, we are utilizing the essential microcontroller, that is to say, Arduino UNO. We were effective in taking readings with the assistance of a sensors and had the option to supply capacity to the UVC light in which it cleaned the articles inside the unit when it was uncovered for 2-3 minutes. Lastly, the robot had the option to move effectively with the assistance of Arduino and Wi-Fi arrangement. All the data will be successfully sent to the Doctor's smartphone using Telegram application and NodeMCufor internet connectivity. © 2022 IEEE.
ABSTRACT
During the Covid-19 pandemic, there was an increase in the use of electrical energy on a household scale. This study developed a home-scale power monitoring system to monitor electrical power at a household scale. This research was conducted to facilitate access to home power monitoring via Android based on the Internet of Things using the Thinger.IO web browser and Telegram Messenger using the Bot feature. This power monitoring system develops using the ACS712 sensor as a current reader and the ZMPT101B as a voltage reader, using an ESP32 microcontroller with a WiFi module that can be connected online. The results of this study are that the accuracy of the ZMPT101B voltage sensor is excellent, with an accuracy value of 99.845%. The ACS712 current sensor has the highest difference value with a reference of 0.32 A and 0.04 A for the lowest difference value. The data logger system on Thinger.IO works well in recording data. The Bot Feature on the Telegram application can work well even though it has an average delay of up to 4.2 seconds, depending on the speed of the internet network. © 2022 IEEE.
ABSTRACT
Purpose: Coronavirus is among the deadliest viruses of the 21st century. There is still a Coronavirus epidemic that affects most countries worldwide today. To prevent future outbreaks and protect public health, it is essential to invest in research and innovation on vaccines, treatments, diagnostic tests, public health infrastructure, and emergency response planning. Additionally, we need to work on mitigation strategies and take a comprehensive and multidisciplinary approach to prevent and fight against the virus. Methods: For the purpose of preventing the spread of microbial organisms, it is essential to take advantage of automatic sanitizer dispensers by deploying them in public places. This is one of the most feasible and effective ways to ensure that people have easy access to hand sanitizer and can reduce the spread of germs. Results: The proposed solution is a contactless sanitizer dispenser with an integrated temperature monitoring system, as well as an alert system for users who exhibit the symptom of infection. Moreover, the proposed solution has added advantage of interfacing with an electronic door so that we can easily implement it at the entrance of a public building/public transportation. This dispenser will also collect data that can be used to identify a symptomatic user and alert the appropriate authorities for safe quarantine. In addition, it is also used to monitor usage metrics, record user entries, and conduct statistical surveys using the ThinkSpeak platform. Conclusions: The proposed model could be a feasible solution to prevent the entry of infected persons and asymptomatic carriers indoors. This can be achieved by implementing automated temperature screening before allowing entry into the building. This can help identify individuals who are potentially infected with the virus and prevent them from entering the premises and potentially spreading the disease to others. Overall, the proposed model is a comprehensive and practical solution that can help to prevent the entry of infected persons and asymptomatic carriers indoors and help to keep the public safe.
ABSTRACT
The lifestyle of the people has changed completely after the COVID-19 pandemic. The virus has also undergone various mutation and causing scare to human existence. Hence, it is important to monitor the health conditions of the faculty members and students before letting them into the college premises. So, we have introduced a system which implements 3 stage screening process. First, it checks whether the visitor is fully vaccinated or not. Then during the second phase, the health condition of the people is monitored. Finally, people without mask are also prevented from entering into college campus. In addition to it, the system also dispenses the hand sanitizing liquid to the visitors. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
One of the efforts to enforce health protocols is the use of body temperature checkers in every public place. Just like on campus, body temperature is checked using a thermometer gun. Problems encountered when checking the health protocol system included temperature data collection and the identity of visitors who entered the campus. Therefore, so that temperature control can be done automatically and visitor history can be viewed and saved automatically every day, body temperature detection and personal identity recognition through E-ID card and photo based on IoT is made. The realization of temperature checks can use the MLX90614 sensor which has the advantage of being able to read body temperature without requiring direct contact between the body and the sensor and is integrated using RFID which uses E-ID as an identity tag and ESP32CAM to take pictures of visitors' faces to be recorded and sent data to the internet. The purpose of this research is to design a body temperature detector and identify self-identity through IoT-based E-ID and Photos and explain the work system and performance of body temperature detectors. From the results of testing for body temperature detection and self-identification through IoT-based E-ID and photos, the results show that this system is able to retrieve temperature data, E-ID, and facial photos. The standard error that occurs during this measurement is 0.03 and the temperature difference between the two tools is 0.18° C. © 2022 IEEE.
ABSTRACT
During this Covid-19-time number of patients in hospital are increased. The covid-19 patients are mainly of two types one who has a serious condition and the other who has a mild covid-19 symptom. On the other way, the patients who have very serious conditions generally have all facilities, they have doctors around them and other medical staff also there to take care of the situation, but the patients who have not very serious conditions are generally isolated in their home, a problem with this home isolated patients are they do not consult with doctor day to day and what happens if patients condition become serious basically this paper is going to solve this two problem and also monitoring the patients while getting different data like a heartbeat, SpO2, body temperature, etc. along with that we used a location sharing and nearest hospitals identification. Here we design IoT, GSM/GPS-based system through which we send the patients' health data directly to the hospital and if the patients' conduction becomes serious then it sends an alert to the hospital along with the patient's location and it also sends the hospital location to the patients. © 2022 IEEE.
ABSTRACT
The lifestyle of the people has changed completely after the COVID-19 pandemic. The virus has also undergone various mutation and causing scare to human existence. Hence, it is important to monitor the health conditions of the faculty members and students before letting them into the college premises. So, we have introduced a system which implements 3 stage screening process. First, it checks whether the visitor is fully vaccinated or not. Then during the second phase, the health condition of the people is monitored. Finally, people without mask are also prevented from entering into college campus. In addition to it, the system also dispenses the hand sanitizing liquid to the visitors. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Due to COVID-19, people have to adapt to the new lifestyle until scientists develop a permanent solution for this pandemic. Monitoring the respiration rate is very important for a COVID-infected person because the Coronavirus infects the pulmonary system of the person. Two problems that arise while monitoring the breath rate are: sensors are contact based and expensive for mass deployment. A conventional wearable breath rate monitoring system burdens the COVID-affected patient and exposes the caregivers to possible transmission. A contactless low-cost breath monitoring system is required, which monitors and records the breath rate continuously. This paper proposes a breath rate monitoring system called COVID-Beat, a wireless, low-cost, and contactless Wi-Fi-based continuous breath monitoring system. This sensor is developed using off-the-shelf commonly available embedded Internet of Thing device ESP32, and the performance is validated by conducting extensive experimentation. The breath rate is estimated by extracting the channel state information of the subcarriers. The system estimates the breath rate with a maximum accuracy of 99% and a minimum accuracy of 91%, achieved by advanced subcarrier selection and fusion method. The experimental results show superior performance over the existing breath rate monitoring technologies.
ABSTRACT
COVID'19 (Corona Virus Disease) has given a warning sign to humanity to either live with nature or the planet will change us for its living. The amount of waste generated during this pandemic is remarkably higher than the usual situation. The most generated waste is single-use plastic like a glove, mask, Personal Protective Equipment (PPE) etc. If this waste is not appropriately managed, it leads to coercion on the ecosystem, wildlife, pollution, and environmental changes. This paper proposes an Alert system for sanitary workers to maintain social distancing while collecting waste from quarantine zones. Also, the collected waste can be video streamed by a mobile-enabled ESP32 CAM device to verify whether the waste has been segregated at the source. © 2022 IEEE.
ABSTRACT
Internet of Things (IoT) is a technology which is rapidly growing, the future of IoT is limitless as the data streams have quadrupled over the years. Future markets are going to shift from traditional data processing techniques to Big Data Analytics and Cloud computing as businesses worldwide are shifting to cloud based work approaches which was largely boosted by the Covid-19 pandemic. Fishes are well known to be highly sensitive to the environment, hence they require proper care and attention from their owners. Many a times they forget to feed the fish, change the water, check the pH levels etc. these problems look simple but when it comes to tracking hundreds of fishes it can be difficult, these issues can be easily resolved by using IoT. An IoT system that can be highly beneficial for small to large scale aquariums is necessary e.g. Dubai Aquarium (where hundreds of fishes are constantly monitored). The System can be used to create the ideal conditions required for high yield. The aquaculture sector is going to play a crucial role in the future economy as fishes are getting scarce all over the world. Steps must be taken to streamline processes and by which increase efficiency while improving fish health. IoT based Aquariums can save Ocean Wildlife by building reliable systems that are capable of real-time data processing. Massive tanks can be built for endangered species in remote locations further increasing biodiversity and building a balanced ecosystem. Larger fishes can be monitored using technologies such as RFID, transmitters, etc. since it can be difficult to monitor them in large tanks. Data received from sensors can be stored in some cloud platform and analyzed for future predictions and redundant storage, all sorts of smart devices are able to communicate with each other regardless of hardware and operating system used. The IoT based Aquarium Monitoring device is capable of capturing the water levels inside the aquarium and notifies the user by email when its low. It can switch on/off the lights of the aquarium, control the automatic feeder using and record the room temperature and humidity readings with the help of AWS technologies. The fish feeder is controlled by the user using a voice application or web/app interface. Parameters used in this project are Room Temperature, Humidity, Water Level, LED status and Feeder status. Sensor acquisition is performed by ESP-32, it is also used as data processing device as well as local server/controller. User can monitor the conditions of the aquarium locally or remotely from any part of the world as long as he/she has an Internet connection since data is processed through AWS Lambda, stored in DynamoDB and hosted in AWS API. Data is further visualized using AWS IoT Analytics and QuickSight for proper decision making. Every feature in this model works effortlessly and is highly accurate. A wide scale Industrial Application of this Project can be included in Aquaponics fish management, fish farming, Zoo keeping, etc. The data received can be used to take necessary actions and are stored for future studies. They are highly beneficial for farmers raising a certain species of fishes and for maintaining a balanced ecology. © 2022 IEEE.
ABSTRACT
With the crisis of the COVID-19 pandemic, it has become apparent in the Philippines that protocols need to be put in place that ensures the health and safety of the people. Included in those protocols is contact tracing and the proper use of masks and shields. The purpose of this research is to develop a system of face mask and face shield detection using image processing with deep learning and thermal scanning for logging system to automate the task of surveying and compliance to wearing of mask and shield. A model for classifying the five classes: face mask, face shield, face mask and face shield, none, and no face was created and trained using the MobileNet architecture, with collected dataset using the Maixduino camera. An overall accuracy of the entire system was found to be at 90%. No face and none classifications have provided results of above 90% in precision, sensitivity, specificity, and F1-Score. While values of the only mask, only shield, and both fluctuate in values in computations, their F1-scores still falls within the range of 80%-90% in performance. The implementation of the MobileNet model on the Maixduino board for was successfully accomplished with considerable classification capability. © 2021 IEEE.
ABSTRACT
The concept of the Internet of Things (IoT) encompasses the connection and monitoring of various remote objects in the real world through the Internet. The COVID-19 is very infectious, and it spreads super-fast by contacting other COVID infected people. There have been few works on COVID detection and prevention in resent time. However, none of the existing works proposed any automatic IoT-based remote blocking system so our work is an autonomous system to stop entering in the campus the COVID suspected. The aim of this work is to detect COVID-19 suspect people and stop them from contacting other people. The proposed system is implemented by using IoT devices. The proposed system first measures the body temperature and Second measures blood oxygen level checks whether it exceeds the World Health Organization (WHO) recommended body temperature and blood oxygen level. In case of high body temperature or low blood oxygen level, the system blocks the person from entering the campus and sends an email to the suspected people notifying their illness. The most advantage of our system is working autonomously, cost-effective, and easy to implement on any campus or office.