ABSTRACT
During the COVID-19 pandemic the healthcare facilities all over world collapsed due to shortage of essential biomedical devices. ECG devices are one of those crucial instruments required for tracing electrical activities of heart. Due to the high cost of gold standard ECG devices used in the medical industries, the availability of on-demand ECG devices was not accessible to everyone. Thus, the need of portable, low cost, on-demand ECG device was needful at the earliest. In this paper we propose a novel, versatile, 3-lead, IoT enabled, LM324/LM741 operational amplifiers in instrumentation amplifier configuration Electrocardiogram machine that is aimed towards providing accurate information about the electrical activity of our heart in real time. In this attempt, we have come up with an analogue circuit design consisting of multiple operational amplifier IC based fundamental circuit blocks. The prototype is designed in such a way that the output of ECG can be visualised worldwide using IoT. © 2023 IEEE.
ABSTRACT
In the current pandemic situation, we need to follow certain precautionary measures to safeguard us from the deadly virus. We have been able to contain the virus to a certain extent through social distancing, by sanitizing ourselves and sterilizing the daily-use items. Monitoring the vitals like body temperature, oxygen saturation, and pulse rate has proven to be effective in diagnosing the fatal disease. In this proposed method, we have come up with a solution to help the user to keep a check on the important parameters mentioned above by incorporating various sensors like MLX90614 non-contact infrared temperature sensor, SpO2 sensor, pulse rate sensor, and ultrasonic sensor in a shirt- CoviGuard. The vitals are displayed on an IOT application called ThingSpeak. A buzzer is used to indicate if the user doesn't maintain the specified distance of 0.5 meters. © 2023 IEEE.
ABSTRACT
The concept of IoT in the current world where speed, accuracy and efficiency are of a high importance, can do wonders if implemented in a structured manner, into a machine, project, hardware, idea which can improve technology. So, IoT has its application in the Events. Events can be of many types and there is a need of man power to handle the events efficiently. People gather in huge numbers if there is a political event, whereas there is limited audience in a cultural show or less people in a marriage function. Any of such events, if handled smartly, can ease the tasks of humans, as well as provide speed and accuracy and ensure proper event management and organization. This project demonstrates a hardware for the entry-exit of people for any event, through the technology of Radio Frequency Identification (RFID), Wireless Fidelity (Wi-Fi), and main heart as ESP 8266 Controller. The software simulation in Cisco Packet Tracer shows a general event organization related to a hotel or government-based area, where different sections are integrated to control and handle the event in a smart way. The use of RFID indicates the contactless operation for monitoring the attendee entry-exit, due to the current COVID-19 protocols. So, such systems are safe and smart to execute. © 2022 IEEE.
ABSTRACT
There is an alarming upward trend in COVID-19 cases, and the existing healthcare system is unable to cater the day-to-day requirements from testing followed by appropriate patient care. The use of monitoring devices has found the importance of detecting the presence of the virus early. In order to expand the exciting monitoring system, every technocrat needed to come forward and donate his money to this. Authors as a responsible persons deemed it proper to work on the development design of multipurpose all in one reliable device to help the front like warriors in identifying persons with COVID-19 symptoms like temperature, heartbeat, humidity and positioning real time. After putting in an extra effort, author has succeeded in translating my idea into action. A device that is so well-designed and will increase the medical brotherhood effort to continue monitoring patient health parameters using a variety of sensors connected to the Arduino board. The generated data is then transmitted via Wi-Fi module to IOT platform, i.e., ThingSpeak and which can be monitored on devices like desktop, laptop or smartphone. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The Covid-19 pandemic has introduced several challenges to the society and safety measures are of utmost importance. Hence, to contain and reduce the spread, mask detection-based entry has emerged as a very fascinating topic in the domains of image processing, computer vision, and the Internet of Things (IoT). Convolutional architectures are being used to develop a number of new algorithms that will improve the accuracy of the algorithm. Such convolutional architectures have also made possible the extraction of pixel details. The project aims to build a binary face classifier which can detect the presence of a mask and accordingly people will be granted entry. The classifier is created by using Convolutional Neural Network (CNN), Region based CNN (R-CNN), ThingSpeak. © 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
Corona virus (COVID-19) is an infectious disease, now this COVID-19 pandemic got spread all over the world which causes illness in the respiratory system in humans, it can spread widely in a short time. In this paper the concept of wireless sensor network (WSN) for Internet of things (IoT) is allocated to the healthcare and detection system for COVID-19 is used to design the biomedical sensors with microcontrollers which are used to collect the data, biosensor based low-cost sensitive portable devices for COVID-19 testing kit which is based on Screen printed electrode sensor (SPEs), this is the complete model of health professionals are observe patients information at the ThingSpeak with help of Wi-Fi, Bluetooth module, professionals workload is minimizing to reducing the possibility of the infected COVID-19 condition. the performance of this work is the data is monitored by the patient's status, the output of these sensors is communicated via wireless sensing node and acquiring for same data has to be send to the remote wireless monitor for the observed patients status via IoT, If in case of any emergency patients can also control the conditions. The stage of infection disease patients can also monitor system data is to inform the medical professionals at the time being finished. Hence the optimistic results show that the biomedical sensors and SPEs are in beneficial process for identification of COVID-19 so it can be situating the results on ThingSpeak and Bluetooth module, The clinical centers to help conditions behind its conformation with additional biomedical sensors. © 2023 The Authors. Published by AnaPub Publications.
ABSTRACT
Telemonitoring has been useful during the COVID19 pandemic, to monitor patients avoiding risk of infection, and patients living in remote areas. Monitoring of SpO2 has been a fundamental parameter to preserve health and go to hospitals only in emergencies. This research develops a prototype of pulse oximetry for telemonitoring using an open-source platform and low-cost elements, the Atmega328 microcontroller and MAX30102 sensor to measure the reflection of light in the blood were used. Our device displays the SpO2 and HR on a screen and through an ESP8266 WiFi module sends the data automatically to a free cloud platform “ThingSpeak”, where it is stored, visualized, or can be exported for analysis in other software. A comparison with a commercial clinical grade device was performed and Bland-Altman charts and ICC to verify the concordance between both. The results are ICC of 0.97 and 0.73 corresponding ±2 BPM and ±3% SpO2 have been obtained. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
With the increasing world population, the need for health prevention is also increasing. In these recent years, there is a rapid advancement in clinical care due to the technological advancements in the various fields of sensors and micro-controllers for assuring fast recovery of patients in the hospitals. The major and crucial necessity of the hospitalized patients is that each patient ought to be provided with a better treatment and observation and ought to be provided the right measure of vital nutrition at the right time. Saline solution is used for the covid patients to reduce the inflammation in different parts of the body such as lungs, heart, kidney and skin. Among the various treatments, the saline therapy is the most important treatment that numerous patients receive from the hospitals. Whenever a saline is fed to the patients, the patient needs to be persistently administered by a nurse or a care-taker. But unfortunately, there are some circumstances like patient's blood flow backwards into the saline tubing system. The proposed saline level monitoring and automatic alert system helps to protect the patients in this Covid time and to provide them with safety during saline feeding hours.
ABSTRACT
Stress is the human body’s response to various factors such as mental, physical, or emotional pressure. Coronavirus Disease 2019 pandemic has disrupted the mental health of most people worldwide. Stress plays a crucial role in corona virus disease patients during their medication period. Therefore, a remote mental health monitoring system has become a necessity. The physiological data captured using body sensors can provide rich information about the stress experienced by a person. Paper proposes a personalized stress indicator for monitoring a person’s mental health through a personalized healthcare platform. The physiological data from body sensors such as the galvanic skin response sensor, electrocardiogram module, and accelerometer module are sent in real-time to an Internet of things platform, ‘ThingSpeak.’ In the ThingSpeak platform, MATLAB analysis is performed to calculate the baseline threshold value of each user. Then, the stress percentage is evaluated based on the data rate above the threshold. The stress percentage is displayed on an output channel of the ThingSpeak platform. It enables remote monitoring of patients’ mental health by sending the health updates to the doctor or caretaker through email. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The Healthcare sector has significantly developed a lot. All Nations started giving more importance to the medical field with the appearance of the new Covid19. But, some countries have been struggling with poor infrastructure in the form of insufficient medical equipment and a shortage of manpower in the medical stream. In such a situation, Remote health monitoring will lighten the burden and ease the process. Currently, smart healthcare is a combination of IoT and cloud architecture. The IoT sensors keep track of patients' health and provide clinically relevant data, which can be used for further processing. If we send all of the raw data generated by the sensors to the cloud for bulk data processing and analysis to make real-time decisions. It would impose several risks such as latency issues, bandwidth congestion, network reliability, high storage cost, and security-related issues which can negatively impact the healthcare industry on whole. To overcome the abovementioned issues, we offer 'Edge Computing, A new emerging technology that allows data processing to be done closer to the data generating device'. Our main aim is to strengthen the existing system. In this paper, the proposed system will continuously collect three main vital parameters from patients in real-time and process the collected data both on the cloud and edge architecture to compare and determine which technology is best suited for time-sensitive applications. © 2022 IEEE.
ABSTRACT
Whenever the patient is admitted to a hospital, the doctors and nurses have to keep a regular check on each of them and also maintain a record of all the vital health parameters of patient. In a situation of pandemic like the one due to COVID-19 a huge number of patients are admitted at once which becomes very difficult for hospital staff to monitor each of them continuously. So, the model proposed here is a IoT based wearable system which is an assistive device for patient monitoring which will help the doctors, nurses and patient's relatives to keep a track of some vital health parameters like heartbeat, temperature and blood oxygen levels. All of these sensor data will be stored into the cloud platform "Thingspeak"and also to the mobile app "Blynk". And this system is made automatic so it will keep on monitoring and storing the sensor data at regular intervals which can be accessed from anywhere via the internet and even the alert system will notify about the emergency. Another part of the model which is separate from the wearable system is to monitor and store volume of drip or IV fluids is given to the patient. © 2022 Copyright for this paper by its authors.
ABSTRACT
With the constant rapid rise in the number of COVID-19 cases, it has become essential for us to always be informed of our body vitals to keep track of any symptoms which we might show. As of now, no solution is discovered by the paramedical industries, so we will have to rely on some other alternative solutions like maintaining social distancing till the medicine is found. We have developed a prototype that can monitor health metrics and the extent to which the employee is vulnerable to COVID-19. At the onset of the COVID-19 pandemic, certain symptoms occur in the affected person. The most common symptoms are elevated body temperature, difficulty breathing, decreased oxygen, decreased pulse, and loss of taste. Considering the main symptoms, i.e. increased body temperature, decreased oxygen level and decreased pulse, prototype is designed with the required sensors and micro-controllers. Subsequently, the sensor data is sent to the cloud and processed through machine learning to determine the employee's vulnerability to COVID-19. So our prototype is a wearable device for the employees that will sense the necessary parameters and send it to the cloud. It also assures social distance is carried out using a dedicated sensor. Once a person is affected by Covid-19, the possibility of spreading is very high, it is important to trace the people who were in contact to the person with corona virus. This way, our prototype can also track contacts that will help break the contact chain. © 2021 IEEE.
ABSTRACT
This project presents a reasonable budget system, designed to help doctors and guardians to monitor the wellness and health condition of their patients even from a distance. This is very important during COVID-19, where there is a need to keep a distance from people. The current monitoring systems at the hospital are mainly wired to bulk equipment for monitoring. There are also monitoring devices that can be used at home. They also have the restriction of movement towards the patient as the devices can only be applied at the bedside of the patient as they are connected by wires to the monitor. As the patient is restricted with their mobility, this interferes with their daily routine and the doctors and nurses at the hospital will have a hard time in keeping updates with the patient's condition. This paper presents an Internet of Things (IoT) based portable patient monitoring system that can be fixed to the remote patient without requiring the patient to be constrained by wires and remain at bed for the whole day. Furthermore, the device can measure and display the health status of a patient which is vital and needed for a better healthcare. Raspberry Pi is used as the central controller for the monitoring system. Sensors sent data through Wi-Fi that is integrated in the Raspberry Pi platform to the database. Similarly, for each of the sensors connected which are LM35 temperature sensor, AD8232 ECG Sensor, MAX30100 pulse oximeter sensor used MQTT server protocol to transmit the data to Node-Red and ThingSpeak for monitoring. The ThingSpeak displays real-time sensors' data and can be monitored on a webpage. An alarm is also sent through ThingTweet if needed. The obtained data from the sensors are saved on a database web page for offline smart pattern analysis in the future for the patient. © IEEE 2021
ABSTRACT
In today's world, everyone's health is a major concern and a top priority. Humans are afflicted with a plethora of diseases because of their unhealthy habits. People are primarily affected by heart attacks and low oxygen levels because of poor medical care and late diagnosis. As a result, this work aims to combat such untimely deaths using smart health monitoring, which employs machine learning and IoT. The proposed system includes ThingSpeak cloud to communicate with the doctor in case of any emergency. This system consists of body temperature sensor, pulse oximeter sensor (for collecting heartbeat rate and oxygen level) and blood pressure sensing module for tracking patient's health. These sensors are interfaced with the Raspberry pi and Arduino Uno microcontroller. The obtained result from patients is continuously monitored and it is updated in LCD and doctor's webpage using Internet of Things. Following these steps, a trained Machine Learning model is used to determine the type of disease being experienced by the patient. This system predicts Normal and two major disease namely Hypertension and Lung disease. By incorporating all these features, we can ensure that people who suffer from heart attacks and lung disease will not die suddenly. The accuracy of this proposed method is 86% approximately in a real time scenario. Furthermore, because raw medical data can be analyzed in a short period of time, the work will aid clinicians in remote monitoring during epidemic situations such as covid. © 2021 IEEE.
ABSTRACT
The recovery from the COVID-19 pandemic hit shows the emergence of increase in quality of life across various parts of the world. With this lifestyle change, people are looking towards high quality food. Fish being a major source of protein, the industry producing fish from aquaculture is booming. The proposed smart aerator system provides an integrated array of underwater systems for selective aeration of the water body. The smart system ensures targeted aeration to guarantee optimal levels of dissolved oxygen at all times. This is beneficial for perfect survival, growth, and reproduction of fishes. The strategically placed spider aerators are turned on when readings from the dissolved oxygen level at the location is below the optimum range of values. The air blower system consists of an intelligent switching system to activate the right aerator based on the requirement. The sensor data is relayed to the cloud with a wireless communication module. This data can be used for useful insights and all-round monitoring of the water body. The respective aerators have IR sensor to detect movement alongside on-board LEDs to indicate functioning status. Overall, this ensures maximum accelerated growth of healthy fishes. Thus, the solution aims at efficiently boosting the ability of the aquaculture industry to meet the ever-growing demand of consumers. © 2022 Institute of Physics Publishing. All rights reserved.
ABSTRACT
Poor indoor environmental quality (IEQ) has become a global concern for World Health Organization (WHO),and its impact on health and well-being has been exacerbated by the COVID-19 pandemic. To monitor and sanitizeindoor air, this study develops a cost-effective and customizable IEQ monitoring system to detect unhealthy andlow-comfort air levels. This system uses ThingSpeak (MATLAB), microcontrollers (Arduino Uno), and variouslow-cost sensors to measure indoor air quality (IAQ) and IEQ in terms of gas, particulate matter, temperature, soundlevel, and ultraviolet (UV) light. The presented system is validated with respect to temperature, relative humidity,and particulate matter by benchmarking against the Camfil air image sensor manufactured by Camfil AB, Stockholm,Sweden. The average error of temperature, relative humidity, and PM2.5 are 0.55%, 5.13%, and 3.45%, respectively © by the authors. Licensee TAETI, Taiwan. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/).
ABSTRACT
The post-COVID-19 era redefines safety and security for all of us. With increasing population, higher rate of unemployment and faster pace of life, we need a solution that can ensure safety as well as peace of mind for the family and their home. The proposed solution Home Shanti provides an integrated and holistic home management system which autonomously and remotely monitors the home without physical presence. It makes use of edge computing mechanisms to take on-board decisions via interaction with the sensors in the IoT environment. Smart home security is offered with a network of specific sensors. In addition, safety of the residents is taken care of in various regions of the house. The system is in constant touch with the owner through cloud, remote monitoring and real-time decision making. Hence, Home Shanti is the perfect solution for the safety and security of urban and rural home environments and its family, truly a ‘shanti’ peace of mind for the homeowner and his/her family. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
With growing health awareness and the increasing cost of medical care, there is an impetus to new and advanced technologies for disease prevention and early diagnosis and treatment. The weakest link exposed by the COVID-19 pandemic in India is health care. Investment in critical health Infrastructure aided by modern technology is the need of the hour. So, this project aims to develop a comprehensive healthcare monitoring system by blending IoT and VLSI. It can monitor a patient’s basic health signs as well as the room condition where the patients are now in real time. We use Nexys4 Artix7 as a processor. In this system, six sensors are used to capture the data from the hospital environment named heartbeat sensor, body, and room temperature sensor, fall detection sensor, blood pressure sensor, air quality monitoring sensors, ECG sensor. The condition of the patients is conveyed via the ThingSpeak website and telephonic calls/SMS to relatives, medical staff. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Water temperature, pH, dissolved oxygen (DO), electrical conductivity (EC), and salinity levels are the critical cultivation factors for freshwater aquaculture. This paper proposes a novel wireless multi-sensor system by integrating the temperature, pH, DO, and EC sensors with an ESP 32 Wi-Fi module for monitoring the water quality of freshwater aquaculture, which acquires the sensing data and salinity information directly derived from the EC level. The information of water temperature, pH, DO, EC, and salinity levels was displayed in the ThingSpeak IoT platform and was visualized in a user-friendly manner by ThingView APP. Firstly, these sensors were integrated with an ESP32 Wi-Fi platform. The observations of sensors and the estimated salinity from the EC level were then transmitted by a Wi-Fi network to an on-site Wi-Fi access point (AP). The acquired information was further transmitted to the ThingSpeak IoT and displayed in the form of a web-based monitoring system which can be directly visualized by online browsing or the ThingView APP. Through the complete processes of pre-calibration, in situ measurement, and post-calibration, the results illustrate that the proposed wireless multi-sensor IoT system has sufficient accuracy, reliable confidence, and a good tolerance for monitoring the water quality of freshwater aquaculture.